DocumentCode :
2015822
Title :
A robust hierarchical probabilistic framework for visual target tracking
Author :
Pyeron, Michael ; Waks, Amir ; Gregoriou, Georghios ; Tretiak, Oleh ; Bar-Kana, Izhak
Author_Institution :
Image Process. Center, Drexel Univ., Philadelphia, PA, USA
fYear :
1991
fDate :
14-17 Apr 1991
Firstpage :
2457
Abstract :
A robust and efficient technique for detection of region boundaries in a sequence of images is the foundation for a hierarchical framework for visual target tracking. This robust technique is a multi-hypothesis test that searches for a boundary that maximizes a certain performance criterion. The framework also consists of a technique to restore noisy images when the parameters are not known and also filtering to predict positions and orientations of successive images
Keywords :
filtering and prediction theory; picture processing; statistical analysis; tracking; boundary detection; filtering; image sequence; noisy images; robust hierarchical probabilistic framework; visual target tracking; Displacement measurement; Fourier transforms; Image motion analysis; Image restoration; Motion analysis; Noise robustness; Optical filters; Shape measurement; Target tracking; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference on
Conference_Location :
Toronto, Ont.
ISSN :
1520-6149
Print_ISBN :
0-7803-0003-3
Type :
conf
DOI :
10.1109/ICASSP.1991.150898
Filename :
150898
Link To Document :
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