The basic computational module of the technique is an old pattern recognition procedure: the mean-shift. In case of gray level feature domain, the spatial information of the target is lost when the background brightness histogram is the same as the target histogram. In this paper, we propose a new algorithm that is independent of background contrast by changing features from a conventional brightness based histogram to a temperature- based histogram. The proposed algorithm can track targets robustly regardless to target-background contrast. The experiment results demonstrate that the temperature-based Mean-Shift outperforms comparing with the brightness-based Mean-Shift when track a object with successive background variations.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
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.