Title
Real-Time Non-rigid Object Tracking Using CAMShift with Weighted Back Projection
Abstract
The Continuously Adaptive Mean Shift algorithm (CAMShift) is an adaptation of mean shift algorithm for object tracking especially for head and face tracking. Traditional CAMShift can not deal with multi-colored object tracking and situations when similar colors exist nearby. In this paper, a new approach towards these problems using CAMShift with weighted back projection is proposed. In our approach, multi-dimensional histogram with thresholding strategy is utilized. And a new back projection weighting strategy is proposed for situations when similar colors exist near the tracked object. Through experiments, the results show that the proposed method exceeds the traditional CAMShift in situations with multi-colored object or similar-colored background while keeping the processing speed real-time.
Year
DOI
Venue
2010
10.1109/ICCSA.2010.39
ICCSA Workshops
Keywords
Field
DocType
real-time non-rigid object tracking,continuously adaptive mean shift algorithm,multicolored object tracking,mean shift algorithm,tracked object,camshift,similar color,weighted back projection,multi-colored object tracking,projection weighting strategy,real time nonrigid object tracking,head tracking,object tracking,object detection,traditional camshift,multi-colored object,mean shift,new approach,face tracking,image colour analysis,production systems,face,kernel,probability distribution,interference,user interfaces,histograms,real time systems,real time,robustness,pixel
Computer vision,Object detection,Histogram,Weighting,Computer science,Robustness (computer science),Video tracking,Artificial intelligence,Thresholding,Mean-shift,Facial motion capture
Conference
ISBN
Citations 
PageRank 
978-1-4244-6462-3
1
0.36
References 
Authors
4
3
Name
Order
Citations
PageRank
Lei Sun12615.36
Bingrong Wang210.70
Takeshi Ikenaga3618125.50