On Space-Time Interest Points
2003 (English)Report (Other academic)
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.
Computer Science Computer Vision and Robotics (Autonomous Systems)
IdentifiersURN: urn:nbn:se:kth:diva-40052OAI: oai:DiVA.org:kth-40052DiVA: diva2:441155
QC 201109232011-09-142011-09-132015-06-03Bibliographically approved