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Optical Engineering

Visual tracking method based on cuckoo search algorithm
Author(s): Ming-Liang Gao; Li-Ju Yin; Guo-Feng Zou; Hai-Tao Li; Wei Liu
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Paper Abstract

Cuckoo search (CS) is a new meta-heuristic optimization algorithm that is based on the obligate brood parasitic behavior of some cuckoo species in combination with the Lévy flight behavior of some birds and fruit flies. It has been found to be efficient in solving global optimization problems. An application of CS is presented to solve the visual tracking problem. The relationship between optimization and visual tracking is comparatively studied and the parameters’ sensitivity and adjustment of CS in the tracking system are experimentally studied. To demonstrate the tracking ability of a CS-based tracker, a comparative study of tracking accuracy and speed of the CS-based tracker with six “state-of-art” trackers, namely, particle filter, meanshift, PSO, ensemble tracker, fragments tracker, and compressive tracker are presented. Comparative results show that the CS-based tracker outperforms the other trackers.

Paper Details

Date Published: 7 July 2015
PDF: 10 pages
Opt. Eng. 54(7) 073105 doi: 10.1117/1.OE.54.7.073105
Published in: Optical Engineering Volume 54, Issue 7
Show Author Affiliations
Ming-Liang Gao, Shandong Univ. of Science and Technology (China)
Li-Ju Yin, Shandong Univ. of Technology (China)
Guo-Feng Zou, Shandong Univ. of Technology (China)
Hai-Tao Li, Shandong Univ. of Technology (China)
Wei Liu, Shandong Univ. of Technology (China)

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