TY - GEN
T1 - A probabilistic framework for segmentation and tracking of multiple non rigid objects for video surveillance
AU - Ivanović, Aleksandar
AU - Huang, Thomas S.
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2004
Y1 - 2004
N2 - This paper presents a probabilistic framework for segmenting and tracking multiple non rigid foreground objects for video surveillance, using a static monocular camera. The algorithm combines information in a probabilistic sense and poses the problem of matching the segmented foreground objects with blobs in the next frame as a non bipartite matching problem. To solve this problem, probability is calculated for each possible matching. Initialization of new objects is also treated in a probabilistic manner. The new framework is shown to be able to handle a greater set of difficult situations and to improve performance significantly.
AB - This paper presents a probabilistic framework for segmenting and tracking multiple non rigid foreground objects for video surveillance, using a static monocular camera. The algorithm combines information in a probabilistic sense and poses the problem of matching the segmented foreground objects with blobs in the next frame as a non bipartite matching problem. To solve this problem, probability is calculated for each possible matching. Initialization of new objects is also treated in a probabilistic manner. The new framework is shown to be able to handle a greater set of difficult situations and to improve performance significantly.
UR - http://www.scopus.com/inward/record.url?scp=20444437647&partnerID=8YFLogxK
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U2 - 10.1109/ICIP.2004.1418763
DO - 10.1109/ICIP.2004.1418763
M3 - Conference contribution
AN - SCOPUS:20444437647
SN - 0780385543
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 353
EP - 356
BT - 2004 International Conference on Image Processing, ICIP 2004
T2 - 2004 International Conference on Image Processing, ICIP 2004
Y2 - 24 October 2004 through 27 October 2004
ER -