TY  - CONF
PB  - IEEE Computer Society
SN  - 9781479946549
Y1  - 2014///
A1  - Mukhtar, A.
A1  - Xia, L.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84906350442&doi=10.1109%2fICIAS.2014.6869447&partnerID=40&md5=eef7de20b8bd402e165a8a83b33586c3
AV  - none
CY  - Kuala Lumpur
ID  - scholars4918
TI  - Target tracking using color based particle filter
KW  - Algorithms; Color; Graphic methods; Lighting; Monte Carlo methods; Signal filtering and prediction; Statistical methods; Surface discharges; Video streaming
KW  -  Background subtraction; Chrominance histograms; Computationally efficient; Corner point; histogram; occlusion; Particle filter; Qualitative evaluations
KW  -  Target tracking
N2  - A robust and efficient visual target tracking algorithm using particle filtering is proposed. Particle filtering has been proven very successful in estimating non-Gaussian and non-linear problems. In this paper, particle filter with color feature estimated the target state with time. Color feature being scale and rotational invariant, have showed robustness to partial occlusion and computationally efficient. The performance is made more robust by choosing the different (YIQ) color scheme. Tracking has been performed by comparison of chrominance histograms of target and candidate positions (particles). The Color based particle filter tracking often leads to inaccurate results when light intensity changes during a video stream. Furthermore, background subtraction has been used for size estimation of target. The qualitative evaluation of proposed algorithm is performed on several real world videos. The experimental results demonstrated that the proposed algorithm can track the moving objects well under illumination changes, occlusion and moving background. © 2014 IEEE.
N1  - cited By 7; Conference of 2014 5th International Conference on Intelligent and Advanced Systems, ICIAS 2014 ; Conference Date: 3 June 2014 Through 5 June 2014; Conference Code:107042
ER  -