Visual tracking method based on cuckoo search algorithm

Ming-Liang Gao; Li-Ju Yin; Guo-Feng Zou; Hai-Tao Li; Wei Liu

doi:10.1117/1.OE.54.7.073105

7 July 2015 Visual tracking method based on cuckoo search algorithm

Ming-Liang Gao, Li-Ju Yin, Guo-Feng Zou, Hai-Tao Li, Wei Liu

Author Affiliations +

Optical Engineering, Vol. 54, Issue 7, 073105 (July 2015). https://doi.org/10.1117/1.OE.54.7.073105

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.

Citation Download Citation

Ming-Liang Gao, Li-Ju Yin, Guo-Feng Zou, Hai-Tao Li, and Wei Liu "Visual tracking method based on cuckoo search algorithm," Optical Engineering 54(7), 073105 (7 July 2015). https://doi.org/10.1117/1.OE.54.7.073105

Published: 7 July 2015

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available