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
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;
Conference_Titel :
Pattern Recognition, 2008. CCPR '08. Chinese Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2316-3
DOI :
10.1109/CCPR.2008.45