Joint estimation fusion and tracking of objects in a single camera using EM-EKF

Pristley Sathyaraj.S; Henry Leung

doi:10.1117/12.2024533

26 September 2013 Joint estimation fusion and tracking of objects in a single camera using EM-EKF

Pristley Sathyaraj.S, Henry Leung

Proceedings Volume 8856, Applications of Digital Image Processing XXXVI; 885617 (2013) https://doi.org/10.1117/12.2024533
Event: SPIE Optical Engineering + Applications, 2013, San Diego, California, United States

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.

Citation Download Citation

Pristley Sathyaraj.S and Henry Leung "Joint estimation fusion and tracking of objects in a single camera using EM-EKF", Proc. SPIE 8856, Applications of Digital Image Processing XXXVI, 885617 (26 September 2013); https://doi.org/10.1117/12.2024533

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