Adaptive Gate Multifeature Bayesian Statistical Tracker

W. B. Schaming

doi:10.1117/12.965948

17 March 1983 Adaptive Gate Multifeature Bayesian Statistical Tracker

W. B. Schaming

Proceedings Volume 0359, Applications of Digital Image Processing IV; (1983) https://doi.org/10.1117/12.965948
Event: 26th Annual Technical Symposium, 1982, San Diego, United States

Abstract

A statistically based tracking algorithm is described which utilizes a powerful segmentation algorithm. Multiple features such as intensity, edge magnitude, and spatial frequency are combined to form a joint probability distribution to characterize a region containing a target and its immediate surround. These distributions are integrated over time to provide a stable estimate of the target region and background statistics. A Bayesian decision rule is implemented using these distributions to classify individual pixels as target or nontarget. An adaptive gate process is used to estimate desired changes in the tracking window size.

Citation Download Citation

W. B. Schaming "Adaptive Gate Multifeature Bayesian Statistical Tracker", Proc. SPIE 0359, Applications of Digital Image Processing IV, (17 March 1983); https://doi.org/10.1117/12.965948

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