DocumentCode
3242321
Title
Color Correlogram Based Particle Filter for Object Tracking
Author
Zhang, Tao ; Fei, Shu-min ; Lu, Hong ; Li, Xiao-dong
Author_Institution
Inst. of Autom., Southeast Univ., Nanjing
fYear
2008
fDate
22-24 Oct. 2008
Firstpage
1
Lastpage
6
Abstract
A novel color correlogram based particle filter was proposed for an object tracking in visual surveillance. By using the color correlogram as object feature, spatial information is incorporated into object representation, which yields a reliable likelihood description of the observation and prediction for tracking the objects accurately. The capability of the tracker to tolerate appearance changes like orientation changes, small scale changes, partial occlusions and background scene changes is demonstrated using real image sequences. Experimental evidence shows that the color correlogram is more effective than the traditional color histogram for objects tracking.
Keywords
Monte Carlo methods; computer vision; feature extraction; image colour analysis; image representation; image sequences; particle filtering (numerical methods); surveillance; target tracking; appearance changes; background scene changes; color correlogram; image sequences; likelihood description; object feature; object representation; object tracking; orientation changes; partial occlusions; particle filter; sequential Monte Carlo method; spatial information; visual surveillance; Automatic control; Control engineering education; Control systems; Electronic mail; Laboratories; Particle filters; Particle measurements; Particle tracking; Reliability engineering; Systems engineering and theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2008. CCPR '08. Chinese Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-2316-3
Type
conf
DOI
10.1109/CCPR.2008.45
Filename
4662998
Link To Document