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Optical Engineering

Feature-driven motion model-based particle-filter tracking method with abrupt motion handling
Author(s): Yu Liu; Shiming Lai; Bin Wang; Maojun Zhang; Wei Wang
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Paper Abstract

The potential for the research of object tracking in computer vision has been well established, but previous object-tracking methods, which consider only continuous and smooth motion, are limited in handling abrupt motions. We introduce an efficient algorithm to tackle this limitation. A feature-driven (FD) motion model-based features from accelerated segment test (FAST) feature matching is proposed in the particle-filtering framework. Various evaluations have demonstrated that this motion model can improve existing methods’ performances to handle abrupt motion significantly. The proposed model can be applied to most existing particle-filter tracking methods.

Paper Details

Date Published: 19 April 2012
PDF: 7 pages
Opt. Eng. 51(4) 047203 doi: 10.1117/1.OE.51.4.047203
Published in: Optical Engineering Volume 51, Issue 4
Show Author Affiliations
Yu Liu, National Univ. of Defense Technology (China)
Shiming Lai, National Univ. of Defense Technology (China)
Bin Wang, National Univ. of Defense Technology (China)
Maojun Zhang, National Univ. of Defense Technology (China)
Wei Wang, National Univ. of Defense Technology (China)

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