Target matching based on multi-view tracking

Yahui Liu; Changsheng Zhou

doi:10.1117/12.872638

24 January 2011 Target matching based on multi-view tracking

Yahui Liu, Changsheng Zhou

Proceedings Volume 7878, Intelligent Robots and Computer Vision XXVIII: Algorithms and Techniques; 78780I (2011) https://doi.org/10.1117/12.872638
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States

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.

Citation Download Citation

Yahui Liu and Changsheng Zhou "Target matching based on multi-view tracking", Proc. SPIE 7878, Intelligent Robots and Computer Vision XXVIII: Algorithms and Techniques, 78780I (24 January 2011); https://doi.org/10.1117/12.872638

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KEYWORDS

Cameras

Target detection

Detection and tracking algorithms

Feature extraction

Particles

Optical flow

Roads

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