Camshift object tracking method with unscented Kalman filtering motion estimation

Da-ke Chen

doi:10.1117/12.970491

15 October 2012 Camshift object tracking method with unscented Kalman filtering motion estimation

Da-ke Chen

Proceedings Volume 8419, 6th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optoelectronic Materials and Devices for Sensing, Imaging, and Solar Energy; 84191K (2012) https://doi.org/10.1117/12.970491
Event: 6th International Symposium on Advanced Optical Manufacturing and Testing Technologies (AOMATT 2012), 2012, Xiamen, China

Abstract

In order to implement real-time tracking of motion object in complex scene of image sequence, a novel tracking method based on Unscented Kalman filtering motion estimation with Camshift theory was introduced. Above all, the motion state of selected object in present frame was estimated with Unscented Kalman filtering, and then the possible position of selected object in next frame was predicted. Finally, the tracked object center was search in adjacent area of the possible position and the object was oriented with histogram color matching principia of Camshift method. Experiment results show that the proposal algorithm can not only effectively solve object sheltered problem induced by sudden motion, but also the tracking performance owing to pose movement is improved. It is very useful for machine controller to provide more precise coordinate error indication.

Citation Download Citation

Da-ke Chen "Camshift object tracking method with unscented Kalman filtering motion estimation", Proc. SPIE 8419, 6th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optoelectronic Materials and Devices for Sensing, Imaging, and Solar Energy, 84191K (15 October 2012); https://doi.org/10.1117/12.970491

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