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On 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KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.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)Report (Other academic)
Abstract [en]

Local image features or interest points provide compact and abstract representations of patterns in an image. In this paper, we extend the notion of spatial interest points into the spatio-temporal domain and show how the resulting features capture interesting events in video and can be used for a compact representation and for interpretation of video data.

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 estimate the spatio-temporal extents of the detected events by maximizing a normalized spatio-temporal Laplacian operator over spatial and temporal scales. To represent the detected events we then compute local, spatio-temporal, scale-invariant N-jets and classify each event with respect to its jet descriptor. For the problem of human motion analysis, we illustrate how video representation in terms of local space-time features allows for detection of walking people in scenes with occlusions and dynamic cluttered backgrounds.

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2003. , 22 p.
National Category
Computer Science Computer Vision and Robotics (Autonomous Systems)
URN: urn:nbn:se:kth:diva-40052OAI: diva2:441155

QC 20110923

Available from: 2011-09-14 Created: 2011-09-13 Last updated: 2015-06-03Bibliographically approved

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