A Probabilistic Framework for Spatio-Temporal Video Representation & Indexing

Authors:
Hayit Greenspan;Jacob Goldberger;Arnoldo Mayer
Affiliations:
-;-;-
Venue:
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Year:
2002

Citing 7
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Abstract

In this work we describe a novel statistical video representation and modeling scheme. Video representation schemes are needed to enable segmenting a video stream into meaningful video-objects, useful for later indexing and retrieval applications. In the proposed methodology, unsupervised clustering via Guassian mixture modeling extracts coherent space-time regions in feature space, and corresponding coherent segments (video-regions) in the video content. A key feature of the system is the analysis of video input as a single entity as opposed to a sequence of separate frames. Space and time are treated uniformly. The extracted space-time regions allow for the detection and recognition of video events. Results of segmenting video content into static vs. dynamic video regions and video content editing are presented.