The week's pick
Random Articles
Reseach Article
Implementation of Hybrid Model of Particle Filter and Kalman Filter based Real-Time Tracking for handling Occlusion on Beagleboard-xM
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 95 - Number 7 |
| Year of Publication: 2014 |
| Authors: Jharna Majumdar, Parashar Dhakal, Nabin Sharma Rijal, Amar Mani Aryal, Nilesh Kumar Mishra |
10.5120/16608-6443
|
Jharna Majumdar, Parashar Dhakal, Nabin Sharma Rijal, Amar Mani Aryal, Nilesh Kumar Mishra . Implementation of Hybrid Model of Particle Filter and Kalman Filter based Real-Time Tracking for handling Occlusion on Beagleboard-xM. International Journal of Computer Applications. 95, 7 ( June 2014), 31-37. DOI=10.5120/16608-6443
Abstract
Particle filter is considered as one of the most robust and accurate techniques in object tracking because of its capability to handle non-linear and non-Gaussian problems. However this technique fails whenever the tracked object is occluded by other objects. In order to solve this problem, in this paper, we have proposed a computer vision based target tracking algorithm that combines both particle filter and Kalman filter. When the target is visible, particle filter is used for tracking the target but whenever there is occlusion, Kalman filter is used to predict and estimate the state of the occluded target. Hence, the proposed algorithm provides accurate results during both visible and occluded conditions. In order to verify the validity and effectiveness of the proposed algorithm, implementation on BeagleBoard-xM, an ARM based embedded platform, has been done. Integration of tracking algorithm on embedded platform paves the way for many real world applications like automated surveillance, human computer interaction, robotics, traffic monitoring etc.
References
- A. P. Li, Z. L. Jing, and S. Q. Hu, "Robust Observation Model for Visual Tracking in Particle Filter", International Journal of Electronics and Communication, Vol. 61, No. 3, pp. 186-194, 2007
- BeagleBoard-xM Rev C System Reference Manual – http://www. beagleboard. org
- Rajbabu Velmurugan,"Implementation Strategies For Particle Filter Based Target Tracking", School of Electrical and Computer Engineering,Georgia Institute of TechnologyMay 2007.
- Jeroen D. Hol, Thomas B. Sch¨on, Fredrik Gustafsson, "On Resampling Algorithms For Particle Filters", Division of Automatic Control,Department of Electrical Engineering, Link¨oping University,SE-581 83, Link¨oping, Sweden.
- Maria Isabel Ribeiro, "Kalman and Extended Kalman Filters:Concept, Derivation andProperties",Institute for Systems and Robotics, Instituto Superior T´ecnico, Av. Rovisco Pais, 11049-001 Lisboa Portugal,2004.
- Ling, H. , Okada, K, "An Efficient Earth Mover's Distance Algorithm for Robust Histogram Comparison", PAMI, 2007.
- S´everine Dubuisson, "The computation of the bhattacharyya distance between histograms without histograms", Laboratoire d'Informatique de Paris 6, Universit´e Pierre et Marie Curie.
- C6Accel Advanced Users Guide http://processors. wiki. ti. com/index. php?title=C6Accel_Advanced_Users_Guide
- Lian Pan, Xiaoming Liu, "The Study of Target Tracking Based on ARM Embedded Platform", Journal of Computers, Vol 7, No 8, pp 2015-2023, August 2012.
- Shen Khang, Vooi Voon Yap, Patrick Sebastian, "Implementation and Optimization of Human Tracking System using ARM Embedded Platform", International Conference on Intelligent & Advanced Systems, Vol 1, pp 353 – 356, June 2012
- GStreamer Manual – http://www. gstreamer. net/
- Simple Directmedia Layer (SDL) – http://www. libsdl. org/
Index Terms
Keywords