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Space-time interest points

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2 Author(s)
I. Laptev ; Dept. of Numerical Anal. & Comput. Sci., Computational Vision & Active Perception Lab., Stockholm, Sweden ; T. Lindeberg

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.

Published in:

Computer Vision, 2003. Proceedings. Ninth IEEE International Conference on

Date of Conference:

13-16 Oct. 2003