Performance of Histogram-Based Skin Colour Segmentation for Arms Detection in Human Motion Analysis Application

Authors: Rosalyn R. Porle, Ali Chekima, Farrah Wong, G. Sainarayanan

Abstract:

Arms detection is one of the fundamental problems in human motion analysis application. The arms are considered as the most challenging body part to be detected since its pose and speed varies in image sequences. Moreover, the arms are usually occluded with other body parts such as the head and torso. In this paper, histogram-based skin colour segmentation is proposed to detect the arms in image sequences. Six different colour spaces namely RGB, rgb, HSI, TSL, SCT and CIELAB are evaluated to determine the best colour space for this segmentation procedure. The evaluation is divided into three categories, which are single colour component, colour without luminance and colour with luminance. The performance is measured using True Positive (TP) and True Negative (TN) on 250 images with manual ground truth. The best colour is selected based on the highest TN value followed by the highest TP value.

Keywords: image colour analysis, image motion analysis, skin, wavelet transform.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1060092

References:

[1] P. Kakumanu, S. Makrogiannis and N. Bourbakis, "A survey of skincolor modelling and detection methods," Pattern Recognition, vol. 40, no. 3, pp. 1106-1122, March, 2007.
[2] J. Mulligan, "Upper Body Pose Estimation from Stereo and Hand-Face Tracking," in Proc. 2nd Canadian Conf. on Computer and Robot Vision, 2005, pp. 413-420.
[3] G. Hua, M. H. Yang and Y. Wu, "Learning to estimate human pose with data driven belief propagation," in Proc. of the IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, 2005, Vol. 2, pp. 747-754.
[4] A. S. Micilotta and R. Bowden, "View-based location and tracking of body parts for visual interaction," in Proc. of British Machine Vision Conference. 2004, vol. 2, pp. 849-858.
[5] S. Mallat, "Wavelets for a vision," Proc. of the IEEE, 1996, vol. 84 (4), pp. 604-614.
[6] T. Acharya, and A. Ray, Image Processing: Principles and Application. John Willey & Sons, 2005.
[7] V. Vezhnevets, V. Sazonov and A. Andreeva, "A Survey on Pixel- Based Skin Color Detection Techniques," in Proc. of GRAPHICON, Moscow, Russia, 2003, pp. 85-92.
[8] S. E. Umbaugh, Computer imaging: digital image analysis and processing. CRC Press, 2005.
[9] J. -C. Terrillon, M. N. Shirazi, H. Fukamachi and S. Akamatsu, "Comparative performance of different skin chrominance models andchrominance spaces for the automatic detection of human faces in color images," in Proc. of 4th IEEE International Conference on Automatic Face and Gesture Recognition, Grenoble, France, 2000, pp. 54-61.
[10] S. Jayaram, S. Schmugge, M. C. Shin and L. V. Tsap, "Effect of colorspace transformation, the illuminance component, and color modeling on skin detection," in Proc. of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004, vol. 2, pp. 813-81.