Space-time Interest Points

Local image features or interest points provide compact ract representations of patterns in an image. In this paper, 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 F?orstner 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...

• Type: Conference
• Year: 2003
• Where: ICCV
• Authors: Ivan Laptev, Tony Lindeberg
• Keywords: Computer Vision, ICCV 2003, Scale-invariant Spatio-temporal Descriptors, Space-time Points, Spatio-temporal Domain, Spatio-temporal Events, Spatio-temporal Extents