Feature selection for reliable tracking using template matching

Authors:
Toshimitsu Kaneko;Osamu Hori
Affiliations:
Multimedia Laboratory, Corporate R&D Center, Toshiba Corporation, Kawasaki, Japan;Multimedia Laboratory, Corporate R&D Center, Toshiba Corporation, Kawasaki, Japan
Venue:
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Year:
2003

Citing 3
Cited 4

SUSAN—A New Approach to Low Level Image Processing

International Journal of Computer Vision
An iterative image registration technique with an application to stereo vision

IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
Visual mapping by a robot rover

IJCAI'79 Proceedings of the 6th international joint conference on Artificial intelligence - Volume 1

Behavioral Priors for Detection and Tracking of Pedestrians in Video Sequences

International Journal of Computer Vision
Object tracking based on the combination of learning and cascade particle filter

SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Robust matching area selection for terrain matching using level set method

ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
Object tracking using particle filter in the wavelet subspace

Neurocomputing

Quantified Score

Hi-index	0.00

Visualization

Abstract

A new feature selection method for reliable tracking is presented. In this paper, it is assumed that features are tracked by template matching where small regions around the features are defined as templates. The proposed method selects features based on the upper bound of the average template matching error. This selection criterion is directly related to the reliability of tracking and hence, the performance is better than that of other feature detectors. Experimental results are presented to confirm the efficiency of the proposed method.