Title
A More Robust Mean Shift Tracker Using Joint Monogenic Signal Analysis and Color Histogram
Abstract
This paper presents a robust object tracking method based on the methodologies of statistical texture analysis of 2D images based on the theory of monogenic signal analysis, jointed with the color histogram. This novel feature extraction method is embedded thereafter in the mean shift framework. Compared with methods of state-of-the-art mean shift trackers, this method proves to be more discriminant and less sensitive to noise. The experimental results proved that our proposed method can achieve robust tracking performances in complex situations with fewer mean shift iterations.
Year
DOI
Venue
2014
10.1109/ICPR.2014.424
Pattern Recognition
Keywords
DocType
ISSN
feature extraction,image colour analysis,image texture,object tracking,statistical analysis,2D images,color histogram,feature extraction method,joint monogenic signal analysis,mean shift framework,robust mean shift tracker,robust object tracking method,statistical texture analysis,mean,monogenic phase,phase quadrant demodulation,shift
Conference
1051-4651
Citations 
PageRank 
References 
2
0.39
5
Authors
4
Name
Order
Citations
PageRank
Oumaima Sliti152.22
habib hamam212423.13
Faouzi Benzarti3158.94
Hamid Amiri48619.36