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.
Space-time interest points
2003-01-01
1052086 byte
Conference paper
Electronic Resource
English
British Library Conference Proceedings | 2003
|British Library Online Contents | 2005
|Image Matching Using Generalized Scale-Space Interest Points
British Library Online Contents | 2015
|British Library Online Contents | 2012
|Time to contact estimation using interest points
IEEE | 2009
|