Object focused simultaneous estimation of optical flow and state dynamics

Bauer, Nicholas J. and Pathirana, Pubudu 2008, Object focused simultaneous estimation of optical flow and state dynamics, in ISSNIP 2008 : IEEE International Conference on Intelligent Sensors, Sensor Networks and Information Processing, IEEE, Piscataway, N.J., pp. 61-66.

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Title Object focused simultaneous estimation of optical flow and state dynamics
Author(s) Bauer, Nicholas J.
Pathirana, Pubudu
Conference name IEEE Conference on Intelligent Sensors, Sensor Networks and Information Processing (2008 : Sydney, N.S.W.)
Conference location Sydney, N.S.W.
Conference dates 15-18 December 2008
Title of proceedings ISSNIP 2008 : IEEE International Conference on Intelligent Sensors, Sensor Networks and Information Processing
Editor(s) Bouzerdoum, A.
Palaniswami, M.
Dissanayake, G.
Sowmya, A.
Publication date 2008
Conference series IEEE Conference on Intelligent Sensors, Sensor Networks and Information Processing
Start page 61
End page 66
Publisher IEEE
Place of publication Piscataway, N.J.
Summary The framework of differential optical flow has been built upon to enhance the performance of motion estimation from optical flow. By coupling optical flow and object state parameters, an effective procedure for object tracking is implemented with the dasiaSimultaneous Estimation of Optical Flow and Object Statepsila (SEOS) technique. The SEOS method utilizes dynamic object parameter information when calculating optical flow for tracking a moving object within a video stream. Optical flow estimation for the SEOS method requires minimization of an error functional containing object physical parameter data. The convergence of an energy functional to a feasible or optimal solution set is not guaranteed. Convergence criteria is often assumed and not shown explicitly. Convergence of the SEOS method for both the Jacobi and Gauss-Seidel numerical resolution methods is evaluated.
ISBN 9781424429578
Language eng
Field of Research 080502 Mobile Technologies
Socio Economic Objective 861302 Automotive Equipment
HERDC Research category E1 Full written paper - refereed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30018213

Document type: Conference Paper
Collection: School of Engineering and Information Technology
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