Differential optical flow methods are widely used within the computer vision community. They are classified as being either local, as in the Lucas-Kanade method, or global, as in the Horn-Schunck technique. As the physical dynamics of an object is inherently coupled into the behavior of its image in the video stream, in this paper, we use such dynamic parameter information in calculating optical flow when tracking a moving object using a video stream. Indeed, we use a modified error function in the minimization that contains physical parameter information. Further, the refined estimates of optical flow is used for better estimation of the physical parameters of the object in the simultaneous estimation of optical flow and object state(SEOS).
History
Event
IEEE International Conference on Networking, Sensing, and Control (4th : 2007 : London)
Pagination
634 - 638
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Location
London, United Kingdom
Place of publication
Piscataway, N.J.
Start date
2007-04-15
End date
2007-04-17
ISBN-13
9781424410767
ISBN-10
1424410762
Language
eng
Publication classification
E1 Full written paper - refereed
Copyright notice
2007, IEEE
Title of proceedings
2007 IEEE International Conference on Networking, Sensing, and Control