Paper Info
Title
Object tracking using Harris corner points based optical flow propagation and Kalman filter
Abstract
This paper proposes an objects tracking method using optical flow information and Kalman filtering. The basic idea of the proposed approach starts from the fact that interesting points based optical flow is more precise and robust when compared to the optical flow of the other pixels of objects. Firstly, objects to be tracked are detected basing on independent component analysis. For each detected object, Harris corner points are extracted and their local optical flow is calculated. The optical flow of the Harris points is then propagated using a Gaussian distribution based technique to estimate the optical flow of the remaining pixels. Finally, the estimated optical flow is corrected using an iterative Kalman Filter. Experimental results on real data set frames are presented to demonstrate the effectiveness and robustness of the method. This work is developed within the framework of the PANsafer project, supported by the ANR VTT program.
Year
DOI
Venue
2011
10.1109/ITSC.2011.6083031
ITSC
Keywords
Field
DocType
gaussian distribution,kalman filters,computer vision,feature extraction,image sequences,independent component analysis,iterative methods,object detection,object tracking,anr vtt program,gaussian distribution based technique,harris corner point based optical flow propagation,pansafer project,iterative kalman filter,object tracking method,optical flow information,real data set frame,kalman filtering,tracking systems,optics
Object detection,Computer vision,Iterative method,Feature extraction,Kalman filter,Robustness (computer science),Video tracking,Artificial intelligence,Pixel,Optical flow,Mathematics
Conference
ISSN
ISBN
Citations 
2153-0009
978-1-4577-2198-4
5
PageRank 
References 
Authors
0.45
6
3
Name
Order
Citations
PageRank
H. Salmane180.83
Yassine Ruichek219845.38
Louahdi Khoudour311714.20