A scale rotation adaptive new mean shift tracking method

Heng Zhang; Lichun Li; You Li; Qifeng Yu

doi:10.1117/12.757134

28 November 2007 A scale rotation adaptive new mean shift tracking method

Heng Zhang, Lichun Li, You Li, Qifeng Yu

Proceedings Volume 6833, Electronic Imaging and Multimedia Technology V; 68330S (2007) https://doi.org/10.1117/12.757134
Event: Photonics Asia 2007, 2007, Beijing, China

Abstract

The mean shift algorithm is an efficient technique for tracking 2D blobs through an image. The scale of the mean shift kernel is a crucial parameter. Classic Mean shift based tracking algorithm uses fixed kernel-bandwidth, which limits the performance when the object scale exceeds the size of the tracking window. Although some modified algorithms can settle the problem of object zooming in a way, these algorithms are helpless to the object rotation. Based on the analysis of the scale-space theory and the current Mean shift algorithms, a scale and rotation adaptive mean shift tracking algorithm is proposed. Experimental results show that the new method can effectively and accurately obtain the best description of the target areas for the first frame, and the new mean shift tracking algorithm can adapt to any kind of object's movements.

Citation Download Citation

Heng Zhang, Lichun Li, You Li, and Qifeng Yu "A scale rotation adaptive new mean shift tracking method", Proc. SPIE 6833, Electronic Imaging and Multimedia Technology V, 68330S (28 November 2007); https://doi.org/10.1117/12.757134

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