@inproceedings{scholars2762, journal = {ICIAS 2012 - 2012 4th International Conference on Intelligent and Advanced Systems: A Conference of World Engineering, Science and Technology Congress (ESTCON) - Conference Proceedings}, pages = {353--356}, year = {2012}, title = {Implementation and optimization of human tracking system using ARM embedded platform}, address = {Kuala Lumpur}, note = {cited By 7; Conference of 2012 4th International Conference on Intelligent and Advanced Systems, ICIAS 2012 ; Conference Date: 12 June 2012 Through 14 June 2012; Conference Code:93534}, volume = {1}, doi = {10.1109/ICIAS.2012.6306217}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84867930507&doi=10.1109\%2fICIAS.2012.6306217&partnerID=40&md5=755dfcab7acd07c7e5a7914381eeac9f}, keywords = {ARM processor; beagleboard; Computer vision applications; Embedded platforms; histogram; Human Tracking; Human tracking systems; Implementation and optimization; Intel corporations; Low Power; opencv; Optimized algorithms; Platform processor; Processing power, Algorithms; Computer vision; Optimization; Tracking (position), Embedded systems}, 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 fight 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 baed on low-power Texas Intruments (TI) DM3730 ARM processor. Functions and library in OpenCV which developed by Intel Corporation was utilized for building the human tracking algorithms. {\^A}{\copyright} 2012 IEEE.}, author = {Teoh, S. K. and Yap, V. V. and Soh, C. S. and Sebastian, P.}, isbn = {9781457719677} }