International Journal of Computer Vision

, Volume 64, Issue 2, pp 107–123

On Space-Time Interest Points


DOI: 10.1007/s11263-005-1838-7

Cite this article as:
Laptev, I. Int J Comput Vision (2005) 64: 107. doi:10.1007/s11263-005-1838-7


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 often reflect interesting events that can be used for a compact representation of video data as well as for interpretation of spatio-temporal events.

To detect spatio-temporal events, we build on the idea of the Harris and Förstner 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 a video representation in terms of local space-time features allows for detection of walking people in scenes with occlusions and dynamic cluttered backgrounds.


interest pointsscale-spacevideo interpretationmatchingscale selection

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Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  1. 1.IRISA/INRIARennes CedexFrance