Adaptive correlation-based tracking algorithm

Mark W. Eklund; Mohan M. Trivedi

doi:10.1117/12.181035

29 July 1994 Adaptive correlation-based tracking algorithm

Mark W. Eklund, Mohan M. Trivedi

Proceedings Volume 2234, Automatic Object Recognition IV; (1994) https://doi.org/10.1117/12.181035
Event: SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994, Orlando, FL, United States

Abstract

The tracking algorithm introduced in this paper was designed with the intent of operation on a pipeline processor. This is different from other algorithms that rely on the branching capabilities which can easily be accomplished by a conventional processor but not pipeline processors. The localization of an object from one frame and the following frame is done using correlation which a pipeline processor handles very well. Finally, little prior knowledge of the object being tracked is required. The heart of this algorithm is the correlation mask. The mask used is a balance between the popular normalized cross correlation filter and the MACE filter. The masks are created from the actual image. Since the object is not a static object, the masks are updated while the object is being tracked. This paper discusses the implementation of this algorithm and its testing.

Citation Download Citation

Mark W. Eklund and Mohan M. Trivedi "Adaptive correlation-based tracking algorithm", Proc. SPIE 2234, Automatic Object Recognition IV, (29 July 1994); https://doi.org/10.1117/12.181035

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