An improved adaptive video tracking method based on mean-shift

Yufeng Li; Fei Liu; Shaohu Gu

doi:10.1117/12.2036943

19 December 2013 An improved adaptive video tracking method based on mean-shift

Yufeng Li, Fei Liu, Shaohu Gu

Proceedings Volume 9045, 2013 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology; 904505 (2013) https://doi.org/10.1117/12.2036943
Event: International Conference on Optical Instruments and Technology (OIT2013), 2013, Beijing, China

Abstract

For the mean shift tracking algorithm, we use the histogram feature which contains little information, but the moving direction and velocity information are not been considered, which leads to the target will be missed easily, what is more, the limitation of traditional algorithm which can not change the size of the window to adapt to the size of target, etc. To overcome those weaknesses, we introduce both the target feature representation idea having the features of adapting to window size adjustment and spatial characteristics and the nature of the kernel function, then, there is no need to estimate the probability for all regions. The results of experiment show that compared with using kalman filtering and mean shift algorithm alone, the weighted mean improved filtering algorithm has greatly improved the instability of target tracking and the robustness of the moving target tracking.

Citation Download Citation

Yufeng Li, Fei Liu, and Shaohu Gu "An improved adaptive video tracking method based on mean-shift", Proc. SPIE 9045, 2013 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, 904505 (19 December 2013); https://doi.org/10.1117/12.2036943

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