DocumentCode :
2795912
Title :
Multi-object filtering from image sequence without detection
Author :
Hoseinnezhad, Reza ; Vo, Ba-Ngu ; Suter, David ; Vo, Ba-Tuong
Author_Institution :
Dept. of Electr. & Electron. Eng., Univ. of Melbourne, Melbourne, VIC, Australia
fYear :
2010
fDate :
14-19 March 2010
Firstpage :
1154
Lastpage :
1157
Abstract :
Almost every single-view visual multi-target tracking method presented in the literature includes a detection routine that maps the image data to point measurements relevant to the target states. These measurements are commonly further processed by a filter to estimate the number of targets and their states. This paper presents a novel visual tracking technique based on a multi-object filtering algorithm that operates directly on the image observations without the need for any detection. Experimental results on tracking sport players show that our proposed method can automatically track numerous interacting targets and quickly finds players entering or leaving the scene.
Keywords :
image sequences; median filters; target tracking; image data; image sequence; multiobject filtering algorithm; multitarget tracking method; visual tracking technique; Bayesian methods; Biological system modeling; Computer science; Data engineering; Filtering; Filters; Image sequences; State estimation; Target tracking; Video sequences; Bayesian estimation; multi-target tracking; object filtering; random finite sets; visual tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on
Conference_Location :
Dallas, TX
ISSN :
1520-6149
Print_ISBN :
978-1-4244-4295-9
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2010.5495370
Filename :
5495370
Link To Document :
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