The effect of colour space on tracking robustness

This paper studies the effect of colour space on the performance of tracking algorithms. The colour spaces that were investigated were grayscale, RGB, YCbCr and HSV. The performance of a normalised cross correlation tracking algorithm was measured to determine robustness and accuracy in the different colour spaces. Track Detection Rate (TDR) and Object Tracking Standard Deviation (OTStd) were used to provide quantitative measures of tracking performance. The combined results indicate that the colour spaces of YCbCr and HSV give more accurate and more robust tracking results compared to grayscale and RGB images. The results also show that the information stored in the chrominance layers of CbCr in the YCbCr colour space and chromaticity layers HS in the HSV colour space, were sufficient for robust tracking. The TDR results range from 93.7% to 97.1% for grayscale and RGB, and 98% to 100% for the YCbCr and HSV colour spaces respectively. A similar trend in the OTStd was observed with a range of 17.0 pixels to 23.9 pixels for grayscale and RGB, and 7.56 pixels to 20.5 pixels for YCbCr and HSV.

[1]  Tim Morris,et al.  Computer Vision and Image Processing: 4th International Conference, CVIP 2019, Jaipur, India, September 27–29, 2019, Revised Selected Papers, Part I , 2020, CVIP.

[2]  Tim Ellis Performance metrics and methods for tracking in surveillance , 2002 .

[3]  Christopher E. Hann,et al.  Fast normalized cross correlation for motion tracking using basis functions , 2006, Comput. Methods Programs Biomed..

[4]  Ming Zhao,et al.  Robust background subtraction in HSV color space , 2002, SPIE ITCom.

[5]  Rafael C. González,et al.  Digital image processing using MATLAB , 2006 .

[6]  Sei-ichiro Kamata,et al.  Lossless compression for RGB color still images , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[7]  Helman Stern,et al.  Adaptive color space switching for face tracking in multi-colored lighting environments , 2002, Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition.

[8]  Jungwon Seo,et al.  Detection of human faces using skin color and eyes , 2000, 2000 IEEE International Conference on Multimedia and Expo. ICME2000. Proceedings. Latest Advances in the Fast Changing World of Multimedia (Cat. No.00TH8532).

[9]  Azriel Rosenfeld,et al.  Computer vision and image processing , 1992 .

[10]  Robert C. Bolles,et al.  Integrating plan-view tracking and color-based person models for multiple people tracking , 2005, IEEE International Conference on Image Processing 2005.

[11]  Wei Niu,et al.  Human activity detection and recognition for video surveillance , 2004, 2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763).

[12]  Yu-Jen Chen,et al.  The Implementation of a Stand-alone Video Tracking and Analysis System for Animal Behavior Measurement in Morris Water Maze , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[13]  N. Papanikolopoulos,et al.  Vision-Based Human Tracking and Activity Recognition , 2003 .

[14]  James E. Black,et al.  A novel method for video tracking performance evaluation , 2003 .

[15]  J. Ohya,et al.  Automatic skin-color distribution extraction for face detection and tracking , 2000, WCC 2000 - ICSP 2000. 2000 5th International Conference on Signal Processing Proceedings. 16th World Computer Congress 2000.

[16]  Horst Bischof,et al.  Performance evaluation metrics for motion detection and tracking , 2004, ICPR 2004.

[17]  Mika Laaksonen,et al.  Skin detection in video under changing illumination conditions , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[18]  Yap Vooi Voon,et al.  Tracking using normalized cross correlation and color space , 2007, 2007 International Conference on Intelligent and Advanced Systems.

[19]  Osama Masoud,et al.  Detection of loitering individuals in public transportation areas , 2005, IEEE Transactions on Intelligent Transportation Systems.

[20]  Woo-Shik Kim,et al.  Interplane prediction for RGB video coding , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[21]  Michael Beetz,et al.  A Person and Context Specific Approach for Skin Color Classification , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[22]  Jiang Li,et al.  Color based multiple people tracking , 2002, 7th International Conference on Control, Automation, Robotics and Vision, 2002. ICARCV 2002..

[23]  Roger D. Boyle,et al.  Performance Evaluation Metrics and Statistics for Positional Tracker Evaluation , 2003, ICVS.

[24]  Luis Enrique Sucar,et al.  Continuous activity recognition with missing data , 2002, Object recognition supported by user interaction for service robots.

[25]  Larry S. Davis,et al.  W4: Real-Time Surveillance of People and Their Activities , 2000, IEEE Trans. Pattern Anal. Mach. Intell..