International Journal of Computer Vision

, Volume 64, Issue 2, pp 107–123

On Space-Time Interest Points

Article

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

Abstract

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.

Keywords

interest pointsscale-spacevideo interpretationmatchingscale selection

Supplementary material

View video

Supplementary material (4.44 MB)

Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  1. 1.IRISA/INRIARennes CedexFrance