International Journal of Image, Graphics and Signal Processing(IJIGSP)

ISSN: 2074-9074 (Print), ISSN: 2074-9082 (Online)

Published By: MECS Press

IJIGSP Vol.5, No.1, Jan. 2013

Driver's Face Tracking Based on Improved CAMShift

Full Text (PDF, 628KB), PP.1-7

Views:120   Downloads:2


Kamarul Hawari Bin Ghazali,Jie Ma,Rui Xiao

Index Terms

Color space, Face tracking, CAMShift, Mean Shift, Probability Distribution Function


The statistic shows that the number of casualty increase in every year due to road accident related to driver drowsiness. After long journey or sleepless night, vehicle driver will perform some bio-features with regard to drowsiness on them face. It is self-evident that getting location information of head in continuous monitoring and surveillance system rapidly and accurately can help prevent many accidents, and consequently save money and reduce personal suffering. In this paper, according the real situation in vehicle, an improved CAMShift approach is proposed to tracking motion of driver’s head. Results from experiment show the significant performance of proposed approach in driver’s head tracking.

Cite This Paper

Kamarul Hawari Bin Ghazali,Jie Ma,Rui Xiao,"Driver's Face Tracking Based on Improved CAMShift", IJIGSP, vol.5, no.1, pp.1-7, 2013.DOI: 10.5815/ijigsp.2013.01.01


[1]Malaysia Sees Increased Road Fatalities. Retrieved June 18, 2011, from 

[2]Reinier Coetzer, Driver fatigue detection based on eye tracking, in Southern Africa Telecommunication Networks and Applications Conference (SATNAC), 2010.

[3]Bradski G R. Computer V ision F ace T racking F or Use i n a Perceptual User In terface[M].Intel T echnology Journal,1998. 

[4]J. G. Allen, R. Y. D. Xu and J. S. Jin, Object tracking using camshift algorithm and multiple quantized feature spaces, in Proceedings of the Pan-Sydney area workshop on Visual information processing, ACM International Conference Proceeding Series Vol. 100 (Australian Computer Society, Inc., Darlinghurst, Australia, 2004).

[5]N. Liu and B. C. Lovell, Mmx-accelerated real-time hand tracking system, in IVCNZ 2001, (Dunedin, New Zealand, 2001). 

[6]Bogdan Kwolek. CamShift - based tracking in joint color-spatial spaces [J] . Computer Analysis of Images and Pat2 terns, 2005 (3691): 693 - 700. 

[7]Z. Zivkovic and B. Krose, An em-like algorithm for color-histogram based object tracking, in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2004. 

[8]Zhaowen Wang, XiaoKang Yang , Yi Xu, CamShift guided particle filter for visual tracking, Signal Processing Systems. China: Shanghai: IEEE Workshop, 2007: 301- 306..

[9]David Exner, Erich Bruns, Daniel Kurz, and Anselm Grundhὅfer, Fast and Robust CAMShift Tracking, in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2010.

[10]Xia Liu, Hongxia Chu, Pingjun Li. Research of the Improved Camshift Tracking Algorithm. IEEE International Conference on Mechatronics and Automation, PP 5-8, August, 2007.

[11]Liu Xue, Chang Faliang, Wang Huajle. An object tracking method based on improved camshift algorithm. Control & Automation.2007,v23, n7-3, p297-298, 305.

[12]penvc Source Computer Vision Library Reference Manual, version 0.001,2000.

[13]HSL and HSV, Retrieved June 18, 2011, from HSL_and_HSV# Hue_and_chroma.

[14]A.R. Smith, “Color Gamut Transform Pairs,”SIGGRAPH 78, pp. 12-19, 1978.

[15]Paul Viola, Michael J. Jones, Robust Real-Time Face Detection, International Journal of Computer Vision 57(2), 2004

[16]Gary R. Bradski, Computer Vision Face Tracking For Use in a Perceptual User Interface, Intel Technology Journal Q2 ’98.

[17]Tian Wei, Zhuang zhenquan, Self-adaptive Skin Color Detection Based on HSV Color Space.[j], Computer Engineering And Applications,2004,14(40):82-85.