Title :
Kernel-Based Spatial-Color Modeling for Fast Moving Object Tracking
Author :
Venkatesh Babu, R. ; Makur, Anuran
Author_Institution :
Dept. of Electr. Eng., Indian Inst. of Sci., Bangalore, India
Abstract :
Visual tracking has been a challenging problem in computer vision over the decades. The applications of visual tracking are far-reaching, ranging from surveillance and monitoring to smart rooms. Mean-shift (MS) tracker, which gained more attention recently, is known for tracking objects in a cluttered environment and its low computational complexity. The major problem encountered in histogram-based MS is its inability to track rapidly moving objects. In order to track fast moving objects, we propose a new robust mean-shift tracker that uses both spatial similarity measure and color histogram-based similarity measure. The inability of MS tracker to handle large displacements is circumvented by the spatial similarity-based tracking module, which lacks robustness to object´s appearance change. The performance of the proposed tracker is better than the individual trackers for tracking fast-moving objects with better accuracy.
Keywords :
computational complexity; image colour analysis; video signal processing; color histogram-based similarity measure; computational complexity; computer vision; fast moving object tracking; histogram-based MS; kernel-based spatial-color modeling; mean-shift tracker; robust mean-shift tracker; spatial similarity measure; spatial similarity-based tracking module; visual tracking; Application software; Background noise; Clustering algorithms; Computational complexity; Computer vision; Computerized monitoring; Kernel; Robustness; Surveillance; Target tracking; Kernel Tracking; Mean-Shift; Object Tracking; Visual Tracking;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
1-4244-0727-3
DOI :
10.1109/ICASSP.2007.366054