The week's pick
Reseach Article
Human Tracking using Particle Filter
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 76 - Number 6 |
| Year of Publication: 2013 |
| Authors: Jharna Majumdar, Kiran S |
10.5120/13248-0710
|
Jharna Majumdar, Kiran S . Human Tracking using Particle Filter. International Journal of Computer Applications. 76, 6 ( August 2013), 1-6. DOI=10.5120/13248-0710
Abstract
Human tracking is the process of locating moving objects (human) over time using camera. It has wide number of applications like security and surveillance, traffic control, video editing, medical imaging etc. It can be a time consuming process due to the large amount of data contained in video. The objective of human tracking is to associate target objects in consecutive video frames. To initiate human tracking an algorithm analyzes video frames and outputs the movement of targets between the frames. There are a number of algorithms each having its own strengths and weakness. Considering the intended use is important when choosing the algorithm. This paper proposes particle filter based methods for human tracking, addressing two major issues such as variations of distance measurement (similarity measure) and Re-Sampling algorithms.
References
- "Video Based Moving Object Tracking by Particle Filter" Md. Zahidul Islam, Chi-Min Oh and Chil-Woo Lee Chonnam National University ,International Journal of Signal Processing, Image Processing and Pattern Vol. 2, No. 1, March, 2009.
- M. G. S. Bruno. Mixed-state particle filters for multi aspect target tracking in image sequences. In Proc. ICASSP, 2003.
- A Novel Particle Filter based on Propagation and PredictionBAI Xiangfeng, LI Aihua, LI Jialei, LIU Taiyang 2011 Third International Conference on Measuring Technology and Mechatronics Automation
- Evaluation of similarity measurement for Image retrieval Dengsheng Zhang and Guojun Lu Gippsland School of Computing and Info Tech, Monash University.
- The Quadratic-Chi Histogram Distance Family. Ofir Pele and Michael Werman School of Computer Science, The Hebrew University of Jerusalem.
- The computation of the bhattacharyya distance between histograms without histograms S´everine Dubuisson Laboratoire d'Informatique de Paris 6, Universit´e Pierre et Marie Curie.
- The Bhattacharyya Metric as an Absolute Similarity Measure for Frequency Coded Data. N. A. Thacker, F. J. Aherne and P. I. Rockett Tina Memo No. 1997-001 Presented at: TIPR'97, Prague 9-11 June, 1997. and publiseed in Kybernetika, 34, 4, 363-368, 1997.
- Kullback-leiber divergence measure in correlation of gray-scale objects. M. Sohail Khalid National University of Sciences and Technology, Pakistan, soh_78@yahoo. com M. Umar Ilyas Khawar Mahmood COMSATS M. Saquib Sarfaraz Technische Universitat, Berlin, Germany M. Bilal Malik . The Second International Conference on Innovations in Information Technology (IIT'05).
- Color Matching of Images by using Minkowski- Form DistanceBy Ajay B. Kurhe, Suhas S. Satonka, Prakash B. Khanale Global Journal of computer science and technology, Volume 11 Issue 5 Version 1. 0 April 2011.
- "Comparison of Resampling Schemes for Particle Filtering Randal Douc, Olivier Capp´e, Eric Moulines, GET T´el´ecom Paris 46 rue Barrault, 75634 Paris, 2010, France.
- ON RESAMPLING ALGORITHMS FOR PARTICLE FILTERS "Jeroen D. Hol, Thomas B. Sch¨on, Fredrik Gustafsson, Division of Automatic Control Department of Electrical Engineering Link¨oping University SE-581 83, Link¨oping, 2008 Sweden.
- Resampling Algorithms for Particle Filters: A Computational Complexity PerspectiveMiodrag Boli´c Petar M. Djuri´c Sangjin Hong Department of Electrical and Computer Engineering, Stony Brook University Stony Brook, New York 11794, USA
- An Efficient Fixed-Point Implementation of Residual Resampling Scheme for High-Speed Particle Filters Sangjin Hong, Member, IEEE, Miodrag Bolic´, Student Member, IEEE, and Petar M. Djuric´, Senior Member, IEEE IEEE SIGNAL PROCESSING LETTERS, VOL. 11, NO. 5, MAY 2004
Index Terms
Keywords