@inproceedings{ea4cedb679ba4fcf9ccd9a4c5e3ec421,
title = "A probabilistic framework for spatio-temporal video representation & indexing",
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.",
author = "Hayit Greenspan and Jacob Goldberger and Arnaldo Mayer",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2002; 7th European Conference on Computer Vision, ECCV 2002 ; Conference date: 28-05-2002 Through 31-05-2002",
year = "2002",
doi = "10.1007/3-540-47979-1_31",
language = "אנגלית",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "461--475",
editor = "Anders Heyden and Gunnar Sparr and Mads Nielsen and Peter Johansen",
booktitle = "Computer Vision - ECCV 2002 - 7th European Conference on Computer Vision, Proceedings",
}