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  • 51.
    Alonso-Fernandez, Fernando
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Englund, Cristofer
    RISE Viktoria, Gothenburg, Sweden.
    Expression Recognition Using the Periocular Region: A Feasibility Study2018Ingår i: 2018 14th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) / [ed] Gabriella Sanniti di Baja, Luigi Gallo, Kokou Yetongnon, Albert Dipanda, Modesto Castrillón-Santana & Richard Chbeir, Los Alamitos: IEEE Computer Society, 2018, s. 536-541Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper investigates the feasibility of using the periocular region for expression recognition. Most works have tried to solve this by analyzing the whole face. Periocular is the facial region in the immediate vicinity of the eye. It has the advantage of being available over a wide range of distances and under partial face occlusion, thus making it suitable for unconstrained or uncooperative scenarios. We evaluate five different image descriptors on a dataset of 1,574 images from 118 subjects. The experimental results show an average/overall accuracy of 67.0%/78.0% by fusion of several descriptors. While this accuracy is still behind that attained with full-face methods, it is noteworthy to mention that our initial approach employs only one frame to predict the expression, in contraposition to state of the art, exploiting several order more data comprising spatial-temporal data which is often not available.

  • 52.
    Alonso-Fernandez, Fernando
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Farrugia, Reuben
    University of Malta, Msida, Malta.
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Very Low-Resolution Iris Recognition Via Eigen-Patch Super-Resolution and Matcher Fusion2016Ingår i: 2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS), Piscataway: IEEE, 2016, artikel-id 7791208Konferensbidrag (Refereegranskat)
    Abstract [en]

    Current research in iris recognition is moving towards enabling more relaxed acquisition conditions. This has effects on the quality of acquired images, with low resolution being a predominant issue. Here, we evaluate a super-resolution algorithm used to reconstruct iris images based on Eigen-transformation of local image patches. Each patch is reconstructed separately, allowing better quality of enhanced images by preserving local information. Contrast enhancement is used to improve the reconstruction quality, while matcher fusion has been adopted to improve iris recognition performance. We validate the system using a database of 1,872 near-infrared iris images. The presented approach is superior to bilinear or bicubic interpolation, especially at lower resolutions, and the fusion of the two systems pushes the EER to below 5% for down-sampling factors up to a image size of only 13×13.

  • 53.
    Alonso-Fernandez, Fernando
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Mikaelyan, Anna
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Compact Multi-scale Periocular Recognition Using SAFE Features2017Ingår i: Proceedings of the 23rd International Conference On Pattern Recognition (Icpr), IEEE Computer Society, 2017, s. 1455-1460, artikel-id 7899842Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper, we present a new approach for periocular recognition based on the Symmetry Assessment by Feature Expansion (SAFE) descriptor, which encodes the presence of various symmetric curve families around image key points. We use the sclera center as single key point for feature extraction, highlighting the object-like identity properties that concentrates to this unique point of the eye. As it is demonstrated, such discriminative properties can be encoded with a reduced set of symmetric curves. Experiments are done with a database of periocular images captured with a digital camera. We test our system against reference periocular features, achieving top performance with a considerably smaller feature vector (given by the use of a single key point). All the systems tested also show a nearly steady correlation between acquisition distance and performance, and they are also able to cope well when enrolment and test images are not captured at the same distance. Fusion experiments among the available systems are also provided. © 2016 IEEE.

  • 54.
    Ambrus, Rares
    KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS. KTH, Skolan för datavetenskap och kommunikation (CSC), Robotik, perception och lärande, RPL.
    Unsupervised construction of 4D semantic maps in a long-term autonomy scenario2017Doktorsavhandling, monografi (Övrigt vetenskapligt)
    Abstract [en]

    Robots are operating for longer times and collecting much more data than just a few years ago. In this setting we are interested in exploring ways of modeling the environment, segmenting out areas of interest and keeping track of the segmentations over time, with the purpose of building 4D models (i.e. space and time) of the relevant parts of the environment.

    Our approach relies on repeatedly observing the environment and creating local maps at specific locations. The first question we address is how to choose where to build these local maps. Traditionally, an operator defines a set of waypoints on a pre-built map of the environment which the robot visits autonomously. Instead, we propose a method to automatically extract semantically meaningful regions from a point cloud representation of the environment. The resulting segmentation is purely geometric, and in the context of mobile robots operating in human environments, the semantic label associated with each segment (i.e. kitchen, office) can be of interest for a variety of applications. We therefore also look at how to obtain per-pixel semantic labels given the geometric segmentation, by fusing probabilistic distributions over scene and object types in a Conditional Random Field.

    For most robotic systems, the elements of interest in the environment are the ones which exhibit some dynamic properties (such as people, chairs, cups, etc.), and the ability to detect and segment such elements provides a very useful initial segmentation of the scene. We propose a method to iteratively build a static map from observations of the same scene acquired at different points in time. Dynamic elements are obtained by computing the difference between the static map and new observations. We address the problem of clustering together dynamic elements which correspond to the same physical object, observed at different points in time and in significantly different circumstances. To address some of the inherent limitations in the sensors used, we autonomously plan, navigate around and obtain additional views of the segmented dynamic elements. We look at methods of fusing the additional data and we show that both a combined point cloud model and a fused mesh representation can be used to more robustly recognize the dynamic object in future observations. In the case of the mesh representation, we also show how a Convolutional Neural Network can be trained for recognition by using mesh renderings.

    Finally, we present a number of methods to analyse the data acquired by the mobile robot autonomously and over extended time periods. First, we look at how the dynamic segmentations can be used to derive a probabilistic prior which can be used in the mapping process to further improve and reinforce the segmentation accuracy. We also investigate how to leverage spatial-temporal constraints in order to cluster dynamic elements observed at different points in time and under different circumstances. We show that by making a few simple assumptions we can increase the clustering accuracy even when the object appearance varies significantly between observations. The result of the clustering is a spatial-temporal footprint of the dynamic object, defining an area where the object is likely to be observed spatially as well as a set of time stamps corresponding to when the object was previously observed. Using this data, predictive models can be created and used to infer future times when the object is more likely to be observed. In an object search scenario, this model can be used to decrease the search time when looking for specific objects.

  • 55.
    Ambrus, Rares
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Robotik, perception och lärande, RPL. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Bore, Nils
    KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Folkesson, John
    KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS. KTH, Skolan för datavetenskap och kommunikation (CSC), Robotik, perception och lärande, RPL.
    Jensfelt, Patric
    KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS. KTH, Skolan för datavetenskap och kommunikation (CSC), Robotik, perception och lärande, RPL.
    Autonomous meshing, texturing and recognition of objectmodels with a mobile robot2017Konferensbidrag (Refereegranskat)
    Abstract [en]

    We present a system for creating object modelsfrom RGB-D views acquired autonomously by a mobile robot.We create high-quality textured meshes of the objects byapproximating the underlying geometry with a Poisson surface.Our system employs two optimization steps, first registering theviews spatially based on image features, and second aligningthe RGB images to maximize photometric consistency withrespect to the reconstructed mesh. We show that the resultingmodels can be used robustly for recognition by training aConvolutional Neural Network (CNN) on images rendered fromthe reconstructed meshes. We perform experiments on datacollected autonomously by a mobile robot both in controlledand uncontrolled scenarios. We compare quantitatively andqualitatively to previous work to validate our approach.

  • 56.
    Ambrus, Rares
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Robotik, perception och lärande, RPL. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Claici, Sebastian
    Wendt, Axel
    Automatic Room Segmentation From Unstructured 3-D Data of Indoor Environments2017Ingår i: IEEE Robotics and Automation Letters, ISSN 2377-3766, E-ISSN 1949-3045, Vol. 2, nr 2, s. 749-756Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We present an automatic approach for the task of reconstructing a 2-D floor plan from unstructured point clouds of building interiors. Our approach emphasizes accurate and robust detection of building structural elements and, unlike previous approaches, does not require prior knowledge of scanning device poses. The reconstruction task is formulated as a multiclass labeling problem that we approach using energy minimization. We use intuitive priors to define the costs for the energy minimization problem and rely on accurate wall and opening detection algorithms to ensure robustness. We provide detailed experimental evaluation results, both qualitative and quantitative, against state-of-the-art methods and labeled ground-truth data.

  • 57.
    Ambrus, Rares
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Ekekrantz, Johan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Folkesson, John
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Jensfelt, Patric
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Unsupervised learning of spatial-temporal models of objects in a long-term autonomy scenario2015Ingår i: 2015 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), IEEE , 2015, s. 5678-5685Konferensbidrag (Refereegranskat)
    Abstract [en]

    We present a novel method for clustering segmented dynamic parts of indoor RGB-D scenes across repeated observations by performing an analysis of their spatial-temporal distributions. We segment areas of interest in the scene using scene differencing for change detection. We extend the Meta-Room method and evaluate the performance on a complex dataset acquired autonomously by a mobile robot over a period of 30 days. We use an initial clustering method to group the segmented parts based on appearance and shape, and we further combine the clusters we obtain by analyzing their spatial-temporal behaviors. We show that using the spatial-temporal information further increases the matching accuracy.

  • 58.
    Ambrus, Rares
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Robotik, perception och lärande, RPL. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Folkesson, John
    KTH, Skolan för datavetenskap och kommunikation (CSC), Robotik, perception och lärande, RPL. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Jensfelt, Patric
    KTH, Skolan för datavetenskap och kommunikation (CSC), Robotik, perception och lärande, RPL. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Unsupervised object segmentation through change detection in a long term autonomy scenario2016Ingår i: IEEE-RAS International Conference on Humanoid Robots, IEEE, 2016, s. 1181-1187Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this work we address the problem of dynamic object segmentation in office environments. We make no prior assumptions on what is dynamic and static, and our reasoning is based on change detection between sparse and non-uniform observations of the scene. We model the static part of the environment, and we focus on improving the accuracy and quality of the segmented dynamic objects over long periods of time. We address the issue of adapting the static structure over time and incorporating new elements, for which we train and use a classifier whose output gives an indication of the dynamic nature of the segmented elements. We show that the proposed algorithms improve the accuracy and the rate of detection of dynamic objects by comparing with a labelled dataset.

  • 59.
    Amigoni, Francesco
    et al.
    Politecnico di Milano, Milan, Italy.
    Yu, Wonpil
    Electronics and Telecommunications Research Institute (ETRI), Daejeon, South Korea.
    Andre, Torsten
    University of Klagenfurt, Klagenfurt, Austria.
    Holz, Dirk
    University of Bonn, Bonn, Germany.
    Magnusson, Martin
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Matteucci, Matteo
    Politecnico di Milano, Milan, Italy.
    Moon, Hyungpil
    Sungkyunkwan University, Suwon, South Korea.
    Yokozuka, Masashi
    Nat. Inst. of Advanced Industrial Science and Technology, Tsukuba, Japan.
    Biggs, Geoffrey
    Nat. Inst. of Advanced Industrial Science and Technology, Tsukuba, Japan.
    Madhavan, Raj
    Amrita University, Clarksburg MD, United States of America.
    A Standard for Map Data Representation: IEEE 1873-2015 Facilitates Interoperability Between Robots2018Ingår i: IEEE robotics & automation magazine, ISSN 1070-9932, E-ISSN 1558-223X, Vol. 25, nr 1, s. 65-76Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The availability of environment maps for autonomous robots enables them to complete several tasks. A new IEEE standard, IEEE 1873-2015, Robot Map Data Representation for Navigation (MDR) [15], sponsored by the IEEE Robotics and Automation Society (RAS) and approved by the IEEE Standards Association Standards Board in September 2015, defines a common representation for two-dimensional (2-D) robot maps and is intended to facilitate interoperability among navigating robots. The standard defines an extensible markup language (XML) data format for exchanging maps between different systems. This article illustrates how metric maps, topological maps, and their combinations can be represented according to the standard.

  • 60.
    Ammenberg, P.
    Uppsala universitet, Fakultetsövergripande enheter, Centrum för bildanalys. Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Analysis of CASI Data - A Case Study From the Archipelago of Stockholm, Sweden2001Ingår i: 6th International Conference, Remote Sensing for Marine and Coastal Environments 2000, Charleston, South Caro, 2001, s. 8 pages-Konferensbidrag (Övrigt vetenskapligt)
  • 61.
    Ammenberg, P.
    Uppsala universitet, Fakultetsövergripande enheter, Centrum för bildanalys. Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Analysis of CASI data - A case study from the archipelago of Stockholm, Sweden2000Ingår i: 6th International Conference, Remote Sensing for Marine and CoastalEnvironments, Charleston, South Carolina, USA, 2000Konferensbidrag (Övrigt vetenskapligt)
  • 62.
    Ammenberg, P.
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Centrum för bildanalys. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för ekologi och evolution, Limnologi. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Flink, P
    Lindell, T.
    Strömbeck, N.
    Bio-optical Modelling Combined with Remote Sensing to Assess Water Quality2002Ingår i: International Journal of Remote Sensing, ISSN 0143-1161, Vol. 23, nr 8, s. 1621-1638Artikel i tidskrift (Refereegranskat)
  • 63.
    Ammenberg, Petra
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Centrum för bildanalys. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Lindell, Tommy
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Centrum för bildanalys. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Automated change detection of bleached coral reef areas2002Ingår i: Proceedings of 7th International Conference, Remote Sensing for Marine and Coastal Environments, 2002Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    Recent dramatic bleaching events on coral reefs have enhanced the need for global environmental monitoring. This paper investigates the value of present high spatial resolution satellites to detect coral bleaching using a change detection technique. We compared an IRS LISS-III image taken during the 1998 bleaching event in Belize to images taken before the bleaching event. The sensitivity of the sensors was investigated and a simulation was made to estimate the effect of sub-pixel changes. A manual interpretation of coral bleaching, based on differences between the images, was performed and the outcome were compared to field observations. The spectral characteristics of the pixels corresponding to the field observations and the manually interpreted bleachings have been analysed and compared to pixels from unaffected areas.

  • 64.
    Amundin, Mats
    et al.
    Kolmården Wildlife Park.
    Hållsten, Henrik
    Filosofiska institutionen, Stockholms universitet.
    Eklund, Robert
    Linköpings universitet, Institutionen för kultur och kommunikation, Avdelningen för språk och kultur. Linköpings universitet, Filosofiska fakulteten.
    Karlgren, Jussi
    Kungliga Tekniska Högskolan.
    Molinder, Lars
    Carnegie Investment Bank, Swedden.
    A proposal to use distributional models to analyse dolphin vocalisation2017Ingår i: Proceedings of the 1st International Workshop on Vocal Interactivity in-and-between Humans, Animals and Robots, VIHAR 2017 / [ed] Angela Dassow, Ricard Marxer & Roger K. Moore, 2017, s. 31-32Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper gives a brief introduction to the starting points of an experimental project to study dolphin communicative behaviour using distributional semantics, with methods implemented for the large scale study of human language.

  • 65.
    Andersson, Adam
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Range Gated Viewing with Underwater Camera2005Självständigt arbete på grundnivå (yrkesexamen), 20 poäng / 30 hpStudentuppsats
    Abstract [en]

    The purpose of this master thesis, performed at FOI, was to evaluate a range gated underwater camera, for the application identification of bottom objects. The master thesis was supported by FMV within the framework of “arbetsorder Systemstöd minjakt (Jan Andersson, KC Vapen)”. The central part has been field trials, which have been performed in both turbid and clear water. Conclusions about the performance of the camera system have been done, based on resolution and contrast measurements during the field trials. Laboratory testing has also been done to measure system specific parameters, such as the effective gate profile and camera gate distances.

    The field trials shows that images can be acquired at significantly longer distances with the tested gated camera, compared to a conventional video camera. The distance where the target can be detected is increased by a factor of 2. For images suitable for mine identification, the increase is about 1.3. However, studies of the performance of other range gated systems shows that the increase in range for mine identification can be about 1.6. Gated viewing has also been compared to other technical solutions for underwater imaging.

  • 66.
    Andersson, Anna
    et al.
    Linköpings universitet, Institutionen för teknik och naturvetenskap.
    Eklund, Klara
    Linköpings universitet, Institutionen för teknik och naturvetenskap.
    A Study of Oriented Mottle in Halftone Print2007Självständigt arbete på avancerad nivå (magisterexamen), 20 poäng / 30 hpStudentuppsats
    Abstract [en]

    Coated solid bleached board belongs to the top-segment of paperboards. One important property of paperboard is the printability. In this diploma work a specific print defect, oriented mottle, has been studied in association with Iggesund Paperboard. The objectives of the work were to develop a method for analysis of the dark and light areas of oriented mottle, to analyse these areas, and to clarify the effect from the print, coating and paperboard surface related factors. This would clarify the origin of oriented mottle and predict oriented mottle on unprinted paperboard. The objectives were fulfilled by analysing the areas between the dark halftone dots, the amount of coating and the ink penetration, the micro roughness and the topography. The analysis of the areas between the dark halftone dots was performed on several samples and the results were compared regarding different properties. The other methods were only applied on a limited selection of samples. The results from the study showed that the intensity differences between the dark halftone dots were enhanced in the dark areas, the coating amount was lower in the dark areas and the ink did not penetrate into the paperboard. The other results showed that areas with high transmission corresponded to dark areas, smoother micro roughness, lower coating amount and high topography. A combination of the information from these properties might be used to predict oriented mottle. The oriented mottle is probably an optical phenomenon in half tone prints, and originates from variations in the coating and other paperboard properties.

  • 67.
    Andersson, Axel
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för fysik.
    Real-Time Feedback for Agility Training: Tracking of reflective markers using a time-of-flight camera2017Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
  • 68.
    Andersson, Carina
    Mälardalens högskola, Akademin för innovation, design och teknik.
    Informationsdesign i tillståndsövervakning: En studie av ett bildskärmsbaserat användargränssnitt för tillståndsövervakning och tillståndsbaserat underhåll2010Doktorsavhandling, monografi (Övrigt vetenskapligt)
    Abstract [en]

    This research concerns the information design and visual design of graphical user interfaces (GUI) in the condition monitoring and condition-based maintenance (CBM) of production equipment. It also concerns various communicative aspects of a GUI, which is used to monitor the condition of assets. It applies to one Swedish vendor and its intentions to design information. In addition, it applies to the interaction between the GUI and its individual visual elements, as well as the communication between the GUI and the users (in four Swedish paper mills).

    The research is performed as a single case study. Interviews and observations have been the main methods for data collection. Empirical data is analyzed with methods inferred to semiotics, rhetoric and narratology. Theories in information science and regarding remediation are used to interpret the user interface design.

    The key conclusion is that there are no less than five different forms of information, all important when determining the conditions of assets. These information forms include the words, images and shapes in the GUI, the machine components and peripherals equipment, the information that takes form when personnel communicate machine conditions, the personnel’s subjective associations, and the information forms that relate to the personnel's actions and interactions.

    Preventive technicians interpret the GUI-information individually and collectively in relation to these information forms, which influence their interpretation and understanding of the GUI information. Social media in the GUI makes it possible to represent essential information that takes form when employees communicate a machine’s condition. Photographs may represent information forms as a machine’s components, peripherals, and local environment change over time. Moreover, preventative technicians may use diagrams and photographs in the GUI to change attitudes among the personnel at the mills and convince them, for example, of a machine’s condition or the effectiveness of CBM as maintenance policy.

  • 69.
    Andersson, Christian
    Linköpings universitet, Institutionen för systemteknik.
    Simulering av filtrerade skärmfärger2005Självständigt arbete på grundnivå (yrkesexamen), 20 poäng / 30 hpStudentuppsats
    Abstract [sv]

    Denna rapport presenterar en fungerande modell för att optiskt simulera vad som händer med färger på bildskärmar då skärmarna betraktas genom optiska filter. Resultat från modellen består av information som kan användas för visuell simulering av en skärm med applicerat filter på en annan visande skärm. Förutom ren bilddata kan modellen även producera färgskillnadsvärden som kan härledas från CIE 1931 XYZ-koordinater. Modellen är datadriven och kräver initiala mätningar på minst den skärm som ska simuleras samt filter. Hela modellen är uppdelad i tre separata moduler eller steg där de olika delarna lätt kan bytas ut för alternativa algoritmer och lösningar. Resultat från undersökningar visar på att modellen går att använda för prototypning även om de, för arbetet specifikt, valda algoritmerna för de olika stegen i undersökningen visar på brister i kvalité. Det finns inget som visar att framtida arbete där andra algoritmer valts inte skulle kunna prestera ännu bättre resultat.

  • 70. Andersson, Jan-Olov
    et al.
    Hasselid, Sara
    Widen, Per
    Bax, Gerhard
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Geovetenskapliga sektionen, Institutionen för geovetenskaper. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Geovetenskapliga sektionen, Institutionen för geovetenskaper, Miljö- och landskapsdynamik. ELD.
    Is the Snow Leopard (Unica unica) endangered?: A study of popular viability and distribution using vulnerability and GIS analysis methods2004Ingår i: Proceedings of the 7th International Symposium on High Mountain Remote Sensing Cartography, 2004, s. 224-Konferensbidrag (Refereegranskat)
  • 71.
    Andersson, Jonathan
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för radiologi, onkologi och strålningsvetenskap, Enheten för radiologi.
    Methods for automatic analysis of glucose uptake in adipose tissue using quantitative PET/MRI data2014Självständigt arbete på avancerad nivå (yrkesexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Brown adipose tissue (BAT) is the main tissue involved in non-shivering heat production. A greater understanding of BAT could possibly lead to new ways of prevention and treatment of obesity and type 2 diabetes. The increasing prevalence of these conditions and the problems they cause society and individuals make the study of the subject important.

    An ongoing study performed at the Turku University Hospital uses images acquired using PET/MRI with 18F-FDG as the tracer. Scans are performed on sedentary and athlete subjects during normal room temperature and during cold stimulation. Sedentary subjects then undergo scanning during cold stimulation again after a six weeks long exercise training intervention. This degree project used images from this study.

    The objective of this degree project was to examine methods to automatically and objectively quantify parameters relevant for activation of BAT in combined PET/MRI data. A secondary goal was to create images showing glucose uptake changes in subjects from images taken at different times.

    Parameters were quantified in adipose tissue directly without registration (image matching), and for neck scans also after registration. Results for the first three subjects who have completed the study are presented. Larger registration errors were encountered near moving organs and in regions with less information.

    The creation of images showing changes in glucose uptake seem to be working well for the neck scans, and somewhat well for other sub-volumes. These images can be useful for identification of BAT. Examples of these images are shown in the report.

  • 72.
    Andersson, Maria
    et al.
    Division of Information Systems, FOI, Swedish Defence Research Agency, Linköping, Sweden.
    Ntalampiras, Stavros
    Department of Electrical and Computer Engineering, University of Patras, Patras, Greece.
    Ganchev, Todor
    Department of Electrical and Computer Engineering, University of Patras, Patras, Greece.
    Rydell, Joakim
    Division of Information Systems, FOI, Swedish Defence Research Agency, Linköping, Sweden.
    Ahlberg, Jörgen
    Division of Information Systems, FOI, Swedish Defence Research Agency, Linköping, Sweden.
    Fakotakis, Nikos
    Department of Electrical and Computer Engineering, University of Patras, Patras, Greece.
    Fusion of Acoustic and Optical Sensor Data for Automatic Fight Detection in Urban Environments2010Ingår i: Information Fusion (FUSION), 2010 13th Conference on, IEEE conference proceedings, 2010, s. 1-8Konferensbidrag (Refereegranskat)
    Abstract [en]

    We propose a two-stage method for detection of abnormal behaviours, such as aggression and fights in urban environment, which is applicable to operator support in surveillance applications. The proposed method is based on fusion of evidence from audio and optical sensors. In the first stage, a number of modalityspecific detectors perform recognition of low-level events. Their outputs act as input to the second stage, which performs fusion and disambiguation of the firststage detections. Experimental evaluation on scenes from the outdoor part of the PROMETHEUS database demonstrated the practical viability of the proposed approach. We report a fight detection rate of 81% when both audio and optical information are used. Reduced performance is observed when evidence from audio data is excluded from the fusion process. Finally, in the case when only evidence from one camera is used for detecting the fights, the recognition performance is poor. 

  • 73.
    Andersson, Maria
    et al.
    FOI Swedish Defence Research Agency.
    Rydell, Joakim
    FOI Swedish Defence Research Agency.
    Ahlberg, Jörgen
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten. FOI Swedish Defence Research Agency.
    Estimation of crowd behaviour using sensor networks and sensor fusion2009Konferensbidrag (Refereegranskat)
    Abstract [en]

    Commonly, surveillance operators are today monitoring a large number of CCTV screens, trying to solve the complex cognitive tasks of analyzing crowd behavior and detecting threats and other abnormal behavior. Information overload is a rule rather than an exception. Moreover, CCTV footage lacks important indicators revealing certain threats, and can also in other respects be complemented by data from other sensors. This article presents an approach to automatically interpret sensor data and estimate behaviors of groups of people in order to provide the operator with relevant warnings. We use data from distributed heterogeneous sensors (visual cameras and a thermal infrared camera), and process the sensor data using detection algorithms. The extracted features are fed into a hidden Markov model in order to model normal behavior and detect deviations. We also discuss the use of radars for weapon detection.

  • 74.
    Andersson, Olov
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Methods for Scalable and Safe Robot Learning2017Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    Robots are increasingly expected to go beyond controlled environments in laboratories and factories, to enter real-world public spaces and homes. However, robot behavior is still usually engineered for narrowly defined scenarios. To manually encode robot behavior that works within complex real world environments, such as busy work places or cluttered homes, can be a daunting task. In addition, such robots may require a high degree of autonomy to be practical, which imposes stringent requirements on safety and robustness. \setlength{\parindent}{2em}\setlength{\parskip}{0em}The aim of this thesis is to examine methods for automatically learning safe robot behavior, lowering the costs of synthesizing behavior for complex real-world situations. To avoid task-specific assumptions, we approach this from a data-driven machine learning perspective. The strength of machine learning is its generality, given sufficient data it can learn to approximate any task. However, being embodied agents in the real-world, robots pose a number of difficulties for machine learning. These include real-time requirements with limited computational resources, the cost and effort of operating and collecting data with real robots, as well as safety issues for both the robot and human bystanders.While machine learning is general by nature, overcoming the difficulties with real-world robots outlined above remains a challenge. In this thesis we look for a middle ground on robot learning, leveraging the strengths of both data-driven machine learning, as well as engineering techniques from robotics and control. This includes combing data-driven world models with fast techniques for planning motions under safety constraints, using machine learning to generalize such techniques to problems with high uncertainty, as well as using machine learning to find computationally efficient approximations for use on small embedded systems.We demonstrate such behavior synthesis techniques with real robots, solving a class of difficult dynamic collision avoidance problems under uncertainty, such as induced by the presence of humans without prior coordination. Initially using online planning offloaded to a desktop CPU, and ultimately as a deep neural network policy embedded on board a 7 quadcopter.

  • 75.
    Andersson, Olov
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem. Linköpings universitet, Tekniska högskolan.
    Heintz, Fredrik
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem. Linköpings universitet, Tekniska högskolan.
    Doherty, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem. Linköpings universitet, Tekniska högskolan.
    Model-Based Reinforcement Learning in Continuous Environments Using Real-Time Constrained Optimization2015Ingår i: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI) / [ed] Blai Bonet and Sven Koenig, AAAI Press, 2015, s. 2497-2503Konferensbidrag (Refereegranskat)
    Abstract [en]

    Reinforcement learning for robot control tasks in continuous environments is a challenging problem due to the dimensionality of the state and action spaces, time and resource costs for learning with a real robot as well as constraints imposed for its safe operation. In this paper we propose a model-based reinforcement learning approach for continuous environments with constraints. The approach combines model-based reinforcement learning with recent advances in approximate optimal control. This results in a bounded-rationality agent that makes decisions in real-time by efficiently solving a sequence of constrained optimization problems on learned sparse Gaussian process models. Such a combination has several advantages. No high-dimensional policy needs to be computed or stored while the learning problem often reduces to a set of lower-dimensional models of the dynamics. In addition, hard constraints can easily be included and objectives can also be changed in real-time to allow for multiple or dynamic tasks. The efficacy of the approach is demonstrated on both an extended cart pole domain and a challenging quadcopter navigation task using real data.

  • 76.
    Andersson, Olov
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Wzorek, Mariusz
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Doherty, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Deep Learning Quadcopter Control via Risk-Aware Active Learning2017Ingår i: Proceedings of The Thirty-first AAAI Conference on Artificial Intelligence (AAAI) / [ed] Satinder Singh and Shaul Markovitch, AAAI Press, 2017, Vol. 5, s. 3812-3818Konferensbidrag (Refereegranskat)
    Abstract [en]

    Modern optimization-based approaches to control increasingly allow automatic generation of complex behavior from only a model and an objective. Recent years has seen growing interest in fast solvers to also allow real-time operation on robots, but the computational cost of such trajectory optimization remains prohibitive for many applications. In this paper we examine a novel deep neural network approximation and validate it on a safe navigation problem with a real nano-quadcopter. As the risk of costly failures is a major concern with real robots, we propose a risk-aware resampling technique. Contrary to prior work this active learning approach is easy to use with existing solvers for trajectory optimization, as well as deep learning. We demonstrate the efficacy of the approach on a difficult collision avoidance problem with non-cooperative moving obstacles. Our findings indicate that the resulting neural network approximations are least 50 times faster than the trajectory optimizer while still satisfying the safety requirements. We demonstrate the potential of the approach by implementing a synthesized deep neural network policy on the nano-quadcopter microcontroller.

  • 77.
    Andersson, Robert
    Linköpings universitet, Institutionen för systemteknik.
    A calibration method for laser-triangulating 3D cameras2008Självständigt arbete på avancerad nivå (yrkesexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    A laser-triangulating range camera uses a laser plane to light an object. If the position of the laser relative to the camera as well as certrain properties of the camera is known, it is possible to calculate the coordinates for all points along the profile of the object. If either the object or the camera and laser has a known motion, it is possible to combine several measurements to get a three-dimensional view of the object.

    Camera calibration is the process of finding the properties of the camera and enough information about the setup so that the desired coordinates can be calculated. Several methods for camera calibration exist, but this thesis proposes a new method that has the advantages that the objects needed are relatively inexpensive and that only objects in the laser plane need to be observed. Each part of the method is given a thorough description. Several mathematical derivations have also been added as appendices for completeness.

    The proposed method is tested using both synthetic and real data. The results show that the method is suitable even when high accuracy is needed. A few suggestions are also made about how the method can be improved further.

  • 78. Andrée, Martin
    et al.
    Paasch, Jesper M.
    Paulsson, Jenny
    Seipel, Stefan
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    BIM and 3D property visualisation2018Ingår i: Proc. FIG Congress 2018, 2018, artikel-id 9367Konferensbidrag (Refereegranskat)
  • 79.
    Anliot, Manne
    Linköpings universitet, Institutionen för systemteknik.
    Volume Estimation of Airbags: A Visual Hull Approach2005Självständigt arbete på grundnivå (yrkesexamen), 20 poäng / 30 hpStudentuppsats
    Abstract [en]

    This thesis presents a complete and fully automatic method for estimating the volume of an airbag, through all stages of its inflation, with multiple synchronized high-speed cameras.

    Using recorded contours of the inflating airbag, its visual hull is reconstructed with a novel method: The intersections of all back-projected contours are first identified with an accelerated epipolar algorithm. These intersections, together with additional points sampled from concave surface regions of the visual hull, are then Delaunay triangulated to a connected set of tetrahedra. Finally, the visual hull is extracted by carving away the tetrahedra that are classified as inconsistent with the contours, according to a voting procedure.

    The volume of an airbag's visual hull is always larger than the airbag's real volume. By projecting a known synthetic model of the airbag into the cameras, this volume offset is computed, and an accurate estimate of the real airbag volume is extracted.

    Even though volume estimates can be computed for all camera setups, the cameras should be specially posed to achieve optimal results. Such poses are uniquely found for different airbag models with a separate, fully automatic, simulated annealing algorithm.

    Satisfying results are presented for both synthetic and real-world data.

  • 80.
    Antonova, Rika
    et al.
    Robotics, Perception and Learning, CSC, Royal Institute of Technology, Stockholm, Sweden.
    Kokic, Mia
    Robotics, Perception and Learning, CSC, Royal Institute of Technology, Stockholm, Sweden.
    Stork, Johannes Andreas
    Robotics, Perception and Learning, CSC, Royal Institute of Technology, Stockholm, Sweden.
    Kragic, Danica
    Robotics, Perception and Learning, CSC, Royal Institute of Technology, Stockholm, Sweden.
    Global Search with Bernoulli Alternation Kernel for Task-oriented Grasping Informed by Simulation2018Ingår i: Proceedings of Machine Learning Research: Conference on Robot Learning 2018, PMLR , 2018, Vol. 87, s. 641-650Konferensbidrag (Refereegranskat)
    Abstract [en]

    We develop an approach that benefits from large simulated datasets and takes full advantage of the limited online data that is most relevant. We propose a variant of Bayesian optimization that alternates between using informed and uninformed kernels. With this Bernoulli Alternation Kernel we ensure that discrepancies between simulation and reality do not hinder adapting robot control policies online. The proposed approach is applied to a challenging real-world problem of task-oriented grasping with novel objects. Our further contribution is a neural network architecture and training pipeline that use experience from grasping objects in simulation to learn grasp stability scores. We learn task scores from a labeled dataset with a convolutional network, which is used to construct an informed kernel for our variant of Bayesian optimization. Experiments on an ABB Yumi robot with real sensor data demonstrate success of our approach, despite the challenge of fulfilling task requirements and high uncertainty over physical properties of objects.

  • 81.
    Anwer, Rao Muhammad
    et al.
    Aalto Univ, Finland.
    Khan, Fahad
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
    Laaksonen, Jorma
    Aalto Univ, Finland.
    Two-Stream Part-based Deep Representation for Human Attribute Recognition2018Ingår i: 2018 INTERNATIONAL CONFERENCE ON BIOMETRICS (ICB), IEEE , 2018, s. 90-97Konferensbidrag (Refereegranskat)
    Abstract [en]

    Recognizing human attributes in unconstrained environments is a challenging computer vision problem. State-of-the-art approaches to human attribute recognition are based on convolutional neural networks (CNNs). The de facto practice when training these CNNs on a large labeled image dataset is to take RGB pixel values of an image as input to the network. In this work, we propose a two-stream part-based deep representation for human attribute classification. Besides the standard RGB stream, we train a deep network by using mapped coded images with explicit texture information, that complements the standard RGB deep model. To integrate human body parts knowledge, we employ the deformable part-based models together with our two-stream deep model. Experiments are performed on the challenging Human Attributes (HAT-27) Dataset consisting of 27 different human attributes. Our results clearly show that (a) the two-stream deep network provides consistent gain in performance over the standard RGB model and (b) that the attribute classification results are further improved with our two-stream part-based deep representations, leading to state-of-the-art results.

  • 82. Arcelli, Carlo
    et al.
    Sanniti di Baja, Gabriella
    Svensson, Stina
    Uppsala universitet, Fakultetsövergripande enheter, Centrum för bildanalys. Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Computing and analysing convex deficiencies to characterise 3D complex objects2005Ingår i: Image and Vision Computing: Discrete Geometry for Computer Imagery, Vol. 23, nr 2, s. 203-211Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Entities such as object components, cavities, tunnels and concavities in 3D digital images can be useful in the framework of object analysis. For each object component, we first identify its convex deficiencies, by subtracting the object component from a covering polyhedron approximating the convex hull. Watershed segmentation is then used to decompose complex convex deficiencies into simpler parts, corresponding to individual cavities, concavities and tunnels of the object component. These entities are finally described by means of a representation system accounting for the shape features characterising them.

  • 83.
    Arnekvist, Isac
    KTH, Skolan för datavetenskap och kommunikation (CSC).
    Reinforcement learning for robotic manipulation2017Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [sv]

    Reinforcement learning har nyligen använts framgångsrikt för att lära icke-simulerade robotar uppgifter med hjälp av en normalized advantage function-algoritm (NAF), detta utan att använda mänskliga demonstrationer. Restriktioner på funktionsytorna som använts kan dock visa sig vara problematiska för generalisering till andra uppgifter. För poseestimering har i liknande sammanhang convolutional neural networks använts med bilder från kamera med konstant position. I vissa applikationer kan dock inte kameran garanteras hålla en konstant position och studier har visat att kvaliteten på policys kraftigt förvärras när kameran förflyttas.

     

    Denna uppsats undersöker användandet av NAF för att lära in en ”pushing”-uppgift med tydliga multimodala egenskaper. Resultaten jämförs med användandet av en deterministisk policy med minimala restriktioner på Q-funktionsytan. Vidare undersöks användandet av convolutional neural networks för pose-estimering, särskilt med hänsyn till slumpmässigt placerade kameror med okänd placering. Genom att definiera koordinatramen för objekt i förhållande till ett synligt referensobjekt så tros relativ pose-estimering kunna utföras även när kameran är rörlig och förflyttningen är okänd. NAF appliceras i denna uppsats framgångsrikt på enklare problem där datainsamling är distribuerad över flera robotar och inlärning sker på en central server. Vid applicering på ”pushing”- uppgiften misslyckas dock NAF, både vid träning på riktiga robotar och i simulering. Deep deterministic policy gradient (DDPG) appliceras istället på problemet och lär sig framgångsrikt att lösa problemet i simulering. Den inlärda policyn appliceras sedan framgångsrikt på riktiga robotar. Pose-estimering genom att använda en fast kamera implementeras också framgångsrikt. Genom att definiera ett koordinatsystem från ett föremål i bilden med känd position, i detta fall robotarmen, kan andra föremåls positioner beskrivas i denna koordinatram med hjälp av neurala nätverk. Dock så visar sig precisionen vara för låg för att appliceras på robotar. Resultaten visar ändå att denna metod, med ytterligare utökningar och modifikationer, skulle kunna lösa problemet.

  • 84.
    Arnekvist, Isac
    et al.
    Robotics, Perception, and Learning lab, Royal Institute of Technology, Stockholm, Sweden.
    Kragic, Danica
    Robotics, Perception, and Learning lab, Royal Institute of Technology, Stockholm, Sweden.
    Stork, Johannes Andreas
    Robotics, Perception, and Learning lab, Royal Institute of Technology, Stockholm, Sweden.
    VPE: Variational Policy Embedding for Transfer Reinforcement Learning2018Manuskript (preprint) (Övrigt vetenskapligt)
  • 85.
    Aronsson, M.
    et al.
    Uppsala universitet, Fakultetsövergripande enheter, Centrum för bildanalys. Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Borgefors, G.
    2D Segmentation and Labelling of Clustered Ring-Shaped Objects2001Konferensbidrag (Refereegranskat)
    Abstract [en]

    A robust segmentation and labelling method to identify individual ring shaped

  • 86.
    Aronsson, M.
    et al.
    Uppsala universitet, Fakultetsövergripande enheter, Centrum för bildanalys. Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Fayyazi, A.
    Comparison of two different approaches for paper volume assembly2000Ingår i: Symposium on Image Analysis - SSAB 2000, 2000, s. 57-60Konferensbidrag (Övrigt vetenskapligt)
  • 87.
    Aronsson, M.
    et al.
    Uppsala universitet, Fakultetsövergripande enheter, Centrum för bildanalys. Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Larsson, K.-A.
    Titta inuti papper -- Looking inside Paper2001Ingår i: Nordisk Papper och Massa, nr 2, s. 44-45Artikel i tidskrift (Övrigt vetenskapligt)
  • 88.
    Aronsson, Mattias
    Uppsala universitet, Fakultetsövergripande enheter, Centrum för bildanalys. Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Estimating Fibre Twist and Aspect Ratios in 3D Voxel Volumes2002Ingår i: International Conference on Pattern Recognition (ICPR'02), 2002Konferensbidrag (Refereegranskat)
  • 89.
    Aronsson Mattias, Henningsson Olle, Sävborg Örjan
    Uppsala universitet, Fakultetsövergripande enheter, Centrum för bildanalys. Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Slice-based Digital Volume Assembly of a Small Paper Sample2002Ingår i: Nordic Pulp and Paper Research Journal, Vol. 17, nr 1Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Digital volume images can be created by assembling a stack of 2D images. By using a microtome for slicing, a Scanning Electron Microscope for imaging and digital analysis tools, we were able to create a small digital volume from a paper sample of Duplex-b

  • 90.
    Aronsson Mattias, Sintorn Ida-Maria
    Uppsala universitet, Fakultetsövergripande enheter, Centrum för bildanalys. Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Ring Shaped Object Detector for Non-Isotropic 2D Images Using Optimized Distance Transform Weights2002Konferensbidrag (Refereegranskat)
    Abstract [en]

    A detector for finding ring shaped objects occurring in clus-ters in 2D images with non-isotropic pixel dimensions have been developed. The rings are characterized as having a closed border and a void interior. We assume that the thick-ness of the rings s

  • 91.
    Aronsson, Mattias
    et al.
    Uppsala universitet, Fakultetsövergripande enheter, Centrum för bildanalys. Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Svensson, Stina
    Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Curvature Measurements for fibres in 3D Images of Paper2002Ingår i: Proceedings SSAB'02 Symposium on Image Analysis, 2002, s. 165-168Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    When analysing fibres in paper using computerised image analysis applied to 3D i mages of paper, one measure of interest is the curvature along each individual fibre and how the curvature changes due to interaction with adjacent fibres. Starting from a cu

  • 92.
    Arvidsson, Lars
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Stereoseende i realtid2007Självständigt arbete på grundnivå (yrkesexamen), 20 poäng / 30 hpStudentuppsats
    Abstract [sv]

    I det här exjobbet har två stereometoder för realtidstillämpningar implementerats och utvärderats. Den ena bygger på blockmatchning och den andra på lokal fas. Målet var att kunna köra metoderna i realtid och undersöka vilken av dem som fungerar bäst. Blockmatchningsmetoden gav gott resultat medan den fasbaserade fungerade sämre, både vad gäller hastighet och precision. SIMD-operationer (Single Instruction Multiple Data) användes hos processorn vilket resulterade en i fördubbling av prestandan.

  • 93.
    Asadi, Sahar
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Fan, Han
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Hernandez Bennetts, Victor
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Lilienthal, Achim
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Time-dependent gas distribution modelling2017Ingår i: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 96, s. 157-170Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Artificial olfaction can help to address pressing environmental problems due to unwanted gas emissions. Sensor networks and mobile robots equipped with gas sensors can be used for e.g. air pollution monitoring. Key in this context is the ability to derive truthful models of gas distribution from a set of sparse measurements. Most statistical gas distribution modelling methods assume that gas dispersion is a time constant random process. While this assumption approximately holds in some situations, it is necessary to model variations over time in order to enable applications of gas distribution modelling in a wider range of realistic scenarios. Time-invariant approaches cannot model well evolving gas plumes, for example, or major changes in gas dispersion due to a sudden change of the environmental conditions. This paper presents two approaches to gas distribution modelling, which introduce a time-dependency and a relation to a time-scale in generating the gas distribution model either by sub-sampling or by introducing a recency weight that relates measurement and prediction time. We evaluated these approaches in experiments performed in two real environments as well as on several simulated experiments. As expected, the comparison of different sub-sampling strategies revealed that more recent measurements are more informative to derive an estimate of the current gas distribution as long as a sufficient spatial coverage is given. Next, we compared a time-dependent gas distribution modelling approach (TD Kernel DM+V), which includes a recency weight, to the state-of-the-art gas distribution modelling approach (Kernel DM+V), which does not consider sampling times. The results indicate a consistent improvement in the prediction of unseen measurements, particularly in dynamic scenarios. Furthermore, this paper discusses the impact of meta-parameters in model selection and compares the performance of time-dependent GDM in different plume conditions. Finally, we investigated how to set the target time for which the model is created. The results indicate that TD Kernel DM+V performs best when the target time is set to the maximum sampling time in the test set.

  • 94.
    Asai, Ryoko
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Kavathatzopoulos, Iordanis
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Robots as companions in feelings and discussions2017Ingår i: Retfærdighed – Justice, Robophilosophy / [ed] Martin Mose Bentzen, Copenhagen, 2017, s. 42-42Konferensbidrag (Refereegranskat)
    Abstract [en]

    Robots are used in emotional relationships. On the other hand, it is not very common to think that robots can be used as partners in a philosophical dialog. It would be challenging to find the conditions under which a robot can be one of the parts in an emotional relationship or in a Socratic dialog. Robots usable as emotional or philosophical companions need probably to function well at both dimensions, providing continuous and interchanging support for feelings and reasoning. Our aim here is not to investigate the technical possibilities for such a machine but the theoretical requirements and ethical conditions for its creation and use.

  • 95. Aslund, M.
    et al.
    Fredenberg, Erik
    KTH, Skolan för teknikvetenskap (SCI), Fysik.
    Telman, M.
    Danielsson, Mats
    KTH, Skolan för teknikvetenskap (SCI), Fysik.
    Detectors for the future of X-ray imaging2010Ingår i: Radiation Protection Dosimetry, ISSN 0144-8420, E-ISSN 1742-3406, Vol. 139, nr 1-3, s. 327-333Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In recent decades, developments in detectors for X-ray imaging have improved dose efficiency. This has been accomplished with for example, structured scintillators such as columnar CsI, or with direct detectors where the X rays are converted to electric charge carriers in a semiconductor. Scattered radiation remains a major noise source, and fairly inefficient anti-scatter grids are still a gold standard. Hence, any future development should include improved scatter rejection. In recent years, photon-counting detectors have generated significant interest by several companies as well as academic research groups. This method eliminates electronic noise, which is an advantage in low-dose applications. Moreover, energy-sensitive photon-counting detectors allow for further improvements by optimising the signal-to-quantum-noise ratio, anatomical background subtraction or quantitative analysis of object constituents. This paper reviews state-of-the-art photon-counting detectors, scatter control and their application in diagnostic X-ray medical imaging. In particular, spectral imaging with photon-counting detectors, pitfalls such as charge sharing and high rates and various proposals for mitigation are discussed.

  • 96.
    Aspers, Patrik
    et al.
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Sociologiska institutionen.
    Fuehrer, Paul
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Sociologiska institutionen.
    Sverrisson, Árni
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Sociologiska institutionen.
    Introduktion2004Ingår i: Bild och samhälle: visuell analys som vetenskaplig metod / [ed] Patrik Aspers, Paul Fuehrer, Árni Sverrisson, Lund: Studentlitteratur, 2004, s. 9-36Kapitel i bok, del av antologi (Övrigt vetenskapligt)
  • 97.
    Assabie Lake, Yaregal
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Multifont recognition System for Ethiopic Script2006Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    In this thesis, we present a general framework for multi-font, multi-size and multi-style Ethiopic character recognition system. We propose structural and syntactic techniques for recognition of Ethiopic characters where the graphically comnplex characters are represented by less complex primitive structures and their spatial interrelationships. For each Ethiopic character, the primitive structures and their spatial interrelationships form a unique set of patterns.

    The interrelationships of primitives are represented by a special tree structure which resembles a binary search tree in the sense that it groups child nodes as left and right, and keeps the spatial position of primitives in orderly manner. For a better computational efficiency, the primitive tree is converted into string pattern using in-order traversal, which generates a base of the alphabet that stores possibly occuring string patterns for each character. The recognition of characters is then achieved by matching the generated patterns with each pattern in a stored knowledge base of characters.

    Structural features are extracted using direction field tensor, which is also used for character segmentation. In general, the recognition system does not need size normalization, thinning or other preprocessing procedures. The only parameter that needs to be adjusted during the recognition process is the size of Gaussian window which should be chosen optimally in relation to font sizes. We also constructed an Ethiopic Document Image Database (EDIDB) from real life documents and the recognition system is tested with respect to variations in font type, size, style, document skewness and document type. Experimental results are reported.

  • 98. Astruc, Marine
    et al.
    Malm, Patrik
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Kumar, Rajesh
    Bengtsson, Ewert
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Cluster detection and field-of-view quality rating: Applied to automated Pap-smear analysis2013Ingår i: Proc. 2nd International Conference on Pattern Recognition Applications and Methods, SciTePress, 2013, s. 355-364Konferensbidrag (Refereegranskat)
    Abstract [en]

    Automated cervical cancer screening systems require high resolution analysis of a large number of epithelial cells, involving complex algorithms, mainly analysing the shape and texture of cell nuclei. This can be a very time consuming process. An initial selection of relevant fields-of-view in low resolution images could limit the number of fields to be further analysed at a high resolution. In particular, the detection of cell clusters is of interest for nuclei segmentation improvement, and for diagnostic purpose, malignant and endometrial cells being more prone to stick together in clusters than other cells. In this paper, we propose methods aiming at evaluating the quality of fields-of-view in bright-field microscope images of cervical cells. The approach consists in the construction of neighbourhood graphs using the nuclei as the set of vertices. Transformations are then applied on such graphs in order to highlight the main structures in the image. The methods result in the delineation of regions with varying cell density and the identification of cell clusters. Clustering methods are evaluated using a dataset of manually delineated clusters and compared to a related work.

  • 99.
    Auer, Cornelia
    et al.
    Zuse Institute Berlin, Berlin, Germany.
    Nair, Jaya
    IIIT – Bangalore, Electronics City, Hosur Road, Bangalore, India.
    Zobel, Valentin
    Zuse Institue Berlin, Berlin, Germany.
    Hotz, Ingrid
    Zuse Institue Berlin, Berlin, Germany.
    2D Tensor Field Segmentation2011Ingår i: Dagstuhl Follow-Ups, E-ISSN 1868-8977, Vol. 2, s. 17-35Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We present a topology-based segmentation as means for visualizing 2D symmetric tensor fields. The segmentation uses directional as well as eigenvalue characteristics of the underlying field to delineate cells of similar (or dissimilar) behavior in the tensor field. A special feature of the resulting cells is that their shape expresses the tensor behavior inside the cells and thus also can be considered as a kind of glyph representation. This allows a qualitative comprehension of important structures of the field. The resulting higher-level abstraction of the field provides valuable analysis. The extraction of the integral topological skeleton using both major and minor eigenvector fields serves as a structural pre-segmentation and renders all directional structures in the field. The resulting curvilinear cells are bounded by tensorlines and already delineate regions of equivalent eigenvector behavior. This pre-segmentation is further adaptively refined to achieve a segmentation reflecting regions of similar eigenvalue and eigenvector characteristics. Cell refinement involves both subdivision and merging of cells achieving a predetermined resolution, accuracy and uniformity of the segmentation. The buildingblocks of the approach can be intuitively customized to meet the demands or different applications. Application to tensor fields from numerical stress simulations demonstrates the effectiveness of our method.

  • 100.
    Augustsson, Louise
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion.
    Study and Analysis of Convolutional Neural Networks for Pedestrian Detection in Autonomous Vehicles2018Självständigt arbete på avancerad nivå (yrkesexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    The automotive industry is heading towards more automation. This puts high demands on many systems like Pedestrian Detection Systems. Such systems need to operate in real time with high accuracy and in embedded systems with limited power, memory resources and compute power. This in turn puts high demands on model size and model design. Lately Convolutional Neural Networks (ConvNets) have dominated the field of object detection and therefore it is reasonable to believe that they are suited for pedestrian detection as well. Therefore, this thesis investigates how ConvNets have been used for pedestrian detection and how such solutions can be implemented in embedded systems on FPGAs (Field Programmable Gate Arrays). The conclusions drawn are that ConvNets indeed perform well on pedestrian detection in terms of accuracy but to a cost of large model sizes and heavy computations. This thesis also comes up with a design proposal of a ConvNet for pedestrian detection with the implementation in an embedded system in mind. The proposed network performs well on pedestrian classification and the performance looks promising for detection as well, but further development is required.

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