Share Email Print

Proceedings Paper

Target matching based on multi-view tracking
Author(s): Yahui Liu; Changsheng Zhou
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

A feature matching method is proposed based on Maximally Stable Extremal Regions (MSER) and Scale Invariant Feature Transform (SIFT) to solve the problem of the same target matching in multiple cameras. Target foreground is extracted by using frame difference twice and bounding box which is regarded as target regions is calculated. Extremal regions are got by MSER. After fitted into elliptical regions, those regions will be normalized into unity circles and represented with SIFT descriptors. Initial matching is obtained from the ratio of the closest distance to second distance less than some threshold and outlier points are eliminated in terms of RANSAC. Experimental results indicate the method can reduce computational complexity effectively and is also adapt to affine transformation, rotation, scale and illumination.

Paper Details

Date Published: 24 January 2011
PDF: 5 pages
Proc. SPIE 7878, Intelligent Robots and Computer Vision XXVIII: Algorithms and Techniques, 78780I (24 January 2011); doi: 10.1117/12.872638
Show Author Affiliations
Yahui Liu, Beijing Information Science and Technology Univ. (China)
Beijing Univ. of Posts and Telecommunications (China)
Changsheng Zhou, Beijing Information Science and Technology Univ. (China)

Published in SPIE Proceedings Vol. 7878:
Intelligent Robots and Computer Vision XXVIII: Algorithms and Techniques
Juha Röning; David P. Casasent; Ernest L. Hall, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?