Infrared target tracking with kernel-based performance metric and eigenvalue-based similarity measure
Applied Optics, Vol. 46, Issue 16, pp. 3239-3252 (2007)
http://dx.doi.org/10.1364/AO.46.003239
Enhanced HTML 
Acrobat PDF (2502 KB)
Abstract
An infrared target tracking framework is presented that consists of three main parts: mean shift tracking, its tracking performance evaluation, and position correction. The mean shift tracking algorithm, which is a widely used kernel-based method, has been developed for the initial tracking for its efficiency and effectiveness. A performance evaluation module is applied for the online evaluation of its tracking performance with a kernel- based metric to unify the tracking and performance metric within a kernel-based tracking framework. Then the tracking performance evaluation result is input into a controller in which a decision is made whether to trigger a position correction process. The position correction module employs a matching method with a new eigenvalue-based similarity measure computed from a local complexity degree weighted covariance matrix. Experimental results on real-life infrared image sequences are presented to demonstrate the efficacy of the proposed method.
© 2007 Optical Society of America
OCIS Codes
(100.0100) Image processing : Image processing
(100.5010) Image processing : Pattern recognition
ToC Category:
Image Processing
History
Original Manuscript: July 17, 2006
Revised Manuscript: October 30, 2006
Manuscript Accepted: January 8, 2007
Published: May 15, 2007
Citation
Jianguo Ling, Erqi Liu, Haiyan Liang, and Jie Yang, "Infrared target tracking with kernel-based performance metric and eigenvalue-based similarity measure," Appl. Opt. 46, 3239-3252 (2007)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-46-16-3239
You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.
Contact your librarian or system administrator
or
Log in to access OSA Member Subscription
You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.
Contact your librarian or system administrator
or
Log in to access OSA Member Subscription
You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.
Contact your librarian or system administrator
or
Log in to access OSA Member Subscription
You do not have subscription access to this journal. Article level metrics are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.
Contact your librarian or system administrator
or
Log in to access OSA Member Subscription
Related Journal Articles 
- Prediction of human observer performance by numerical observers: an experimental study (JOSAA)
- Three-dimensional object recognition by use of digital holography (OL)
- Methods to obtain quantitative parametric descriptions of the optical surfaces of the human crystalline lens from Scheimpflug slit-lamp images. I. Image processing methods (JOSAA)
- Unified statistically independent region processor for deterministic and fluctuating targets in nonoverlapping background (OL)
- Improvement in robustness of the statistically independent region snake-based segmentation method of target-shape tracking (OL)
Related Conference Papers
- Integrated Sensing and Processing for Target Detection in Multi-Spectral data
- Template construction for object and biometric recognition
- Quantitative Histo- and Cytopathology
- Characterization of a Harmful Algal Bloom in Monterey Bay, CA Using Airborne Hyperspectral Imagery
- Photon Counting 3-D Passive Sensing and Object Recognition
« Previous Article | Next Article »
OSA is a member of 