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Proceedings Paper

Joint estimation fusion and tracking of objects in a single camera using EM-EKF
Author(s): Pristley Sathyaraj.S; Henry Leung
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Paper Abstract

Tracking objects in dynamic scene is an interesting area of research and it has it's applications in many areas like surveillance, missile tracking system,virtual reality and robot vision. Objects in real world exhibit complex interactions with each other. When captured in a video signal, these interactions manifest themselves as in- tertwineing motions , occlusion and pose changes. A video tracking system should track these objects in this complex interactions smoothly . This paper presents a new joint method for tracking moving objects in outdoor and indoor environment. This joint method uses recursive Expectation-Maximization (EM) incorporated with Extended Kalman Filter (EKF) to estimate, fuse and track the object simultaneously, than doing it in two dif- ferent steps. This combined approach provides more realistic solution to the problem. Thereby, outperforming the conventional method of treating it as three di erent problems. We have tested our algorithm with standard dataset and real time video sequences collected from indoor environment. We also nd that the usage of the joint method improves the accuracy and computational cost. This method successfully tracks object with occlusions, di erent orientations and intertwining motion.

Paper Details

Date Published: 26 September 2013
PDF: 10 pages
Proc. SPIE 8856, Applications of Digital Image Processing XXXVI, 885617 (26 September 2013); doi: 10.1117/12.2024533
Show Author Affiliations
Pristley Sathyaraj.S, Univ. of Calgary (Canada)
Henry Leung, Univ. of Calgary (Canada)


Published in SPIE Proceedings Vol. 8856:
Applications of Digital Image Processing XXXVI
Andrew G. Tescher, Editor(s)

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