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Vol. 17, Special Issue, December 2012, pp. 226-233


Selected papers from the 4th International Conference on Intelligent & Advanced Systems (ICIAS' 2012),

12-14 June 2012, Malaysia, Kuala Lumpur




Implementation and Optimization of Human Tracking System Using ARM Embedded Platform

1 Shen Khang TEOH, 2 Vooi Voon YAP, 2 Chit Siang SOH, 3 Patrick Sebastian

1 Department of Computer and Communication Technology

Centre for Information Systems and Software Technologies (CISST),

 Universiti Tunku Abdul Rahman, Perak, Malaysia

2 Department of Electronic Engineering, Faculty of Engineering and Green Technology

Universiti Tunku Abdul Rahman, Perak, Malaysia

3 Department of Electrical and Electronic Engineering,

Universiti Teknologi PETRONAS, Perak, Malaysia

E-mail: teohsk@utar.edu.my, vvyap@utar.edu.my, sohcs@utar.edu.my, Patrick_sebastian@petronas.com.my



Received: 29 September 2012   /Accepted: 29 October 2012   /Published: 18 December 2012

Digital Sensors and Sensor Sysstems


Abstract: Computer vision is a field that includes methods for acquiring, processing, analyzing and understanding images. In the embedded world, computer vision applications have to deal with limited processing power and limited resources to achieve optimized algorithms and high performance. This paper presents work on implementing a human tracking system on both Intel based PC platform and embedded systems to optimize the algorithms for high performance. The algorithms are benchmarked on the Intel platform processor and BeagleBoard xM based on low-power Texas Instruments (TI) DM3730 ARM processor. Functions and library in OpenCV which developed by Intel Corporation was utilized for building the human tracking algorithms.


Keywords: Human tracking, OpenCV, Histogram, Beagleboard



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