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Visual Object Detection using Convolutional Neural Networks in a Virtual Environment
Linköping University, Department of Electrical Engineering, Computer Vision.
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Visual object detection is a popular computer vision task that has been intensively investigated using deep learning on real data. However, data from virtual environments have not received the same attention. A virtual environment enables generating data for locations that are not easily reachable for data collection, e.g. aerial environments. In this thesis, we study the problem of object detection in virtual environments, more specifically an aerial virtual environment. We use a simulator, to generate a synthetic data set of 16 different types of vehicles captured from an airplane.

To study the performance of existing methods in virtual environments, we train and evaluate two state-of-the-art detectors on the generated data set. Experiments show that both detectors, You Only Look Once version 3 (YOLOv3) and Single Shot MultiBox Detector (SSD), reach similar performance quality as previously presented in the literature on real data sets.

In addition, we investigate different fusion techniques between detectors which were trained on two different subsets of the dataset, in this case a subset which has cars with fixed colors and a dataset which has cars with varying colors. Experiments show that it is possible to train multiple instances of the detector on different subsets of the data set, and combine these detectors in order to boost the performance.

Place, publisher, year, edition, pages
2019. , p. 63
Keywords [en]
Object Detection, Convolutional Neural Networks, Virtual Environment, Computer Vision, Deep Learning, Machine Learning
National Category
Computer Engineering
Identifiers
URN: urn:nbn:se:liu:diva-156609ISRN: LiTH-ISY-EX–19/5195–SEOAI: oai:DiVA.org:liu-156609DiVA, id: diva2:1307568
External cooperation
Saab Aeronautics
Subject / course
Computer Vision Laboratory
Presentation
2019-04-12, Stora konferensrum Visionen, 581 83 Linköping, Linköping, 10:15 (English)
Supervisors
Examiners
Available from: 2019-05-02 Created: 2019-04-28 Last updated: 2019-05-13Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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Output format
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