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Space-time interest points
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.ORCID iD: 0000-0002-9081-2170
2003 (English)In: Proceedings of Ninth IEEE International Conference on Computer Vision, 2003: ICCV'03, IEEE conference proceedings, 2003, 432-439 p.Conference paper (Refereed)
Abstract [en]

Local image features or interest points provide compact and abstract representations of patterns in an image. We propose to extend the notion of spatial interest points into the spatio-temporal domain and show how the resulting features often reflect interesting events that can be used for a compact representation of video data as well as for its interpretation. To detect spatio-temporal events, we build on the idea of the Harris and Forstner interest point operators and detect local structures in space-time where the image values have significant local variations in both space and time. We then estimate the spatio-temporal extents of the detected events and compute their scale-invariant spatio-temporal descriptors. Using such descriptors, we classify events and construct video representation in terms of labeled space-time points. For the problem of human motion analysis, we illustrate how the proposed method allows for detection of walking people in scenes with occlusions and dynamic backgrounds.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2003. 432-439 p.
Keyword [en]
Acceleration, Computer vision, Event detection, Image motion analysis, Indexing, Layout, Motion analysis, Optical computing, Spatiotemporal phenomena, Videoconference
National Category
Computer Science Computer Vision and Robotics (Autonomous Systems) Mathematics
URN: urn:nbn:se:kth:diva-40196DOI: 10.1109/ICCV.2003.1238378OAI: diva2:442088
9th International Conference on Computer Vision, Nice, France

QC 20110920

Available from: 2013-04-22 Created: 2011-09-13 Last updated: 2013-04-22Bibliographically approved

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