2000 fps real-time target tracking vision system based on color histogram

Idaku Ishii; Tetsuro Tatebe; Qingyi Gu; Takeshi Takaki

doi:10.1117/12.871936

2 February 2011 2000 fps real-time target tracking vision system based on color histogram

Idaku Ishii, Tetsuro Tatebe, Qingyi Gu, Takeshi Takaki

Author Affiliations +

Proceedings Volume 7871, Real-Time Image and Video Processing 2011; 787103 (2011) https://doi.org/10.1117/12.871936
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States

Abstract

In this study, we develop a high-speed color-histogram-based tracking system that can be applied to 512x511 pixel images at 2000~fps using the hardware implementation of an improved CamShift algorithm. In the improved algorithm, the size, position, and orientation of an object to be tracked can be extracted using only the hardware implementation of color conversion and the moment feature calculation of 16 binary images quantized by color bins on a high-speed vision platform. We demonstrate its effectiveness by presenting several target tracking results at 2000~fps when color-patterned objects move rapidly under complicated backgrounds.

Citation Download Citation

Idaku Ishii, Tetsuro Tatebe, Qingyi Gu, and Takeshi Takaki "2000 fps real-time target tracking vision system based on color histogram", Proc. SPIE 7871, Real-Time Image and Video Processing 2011, 787103 (2 February 2011); https://doi.org/10.1117/12.871936

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