Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30184
Extracting Human Body based on Background Estimation in Modified HLS Color Space

Authors: Jang-Hee Yoo, Doosung Hwang, Jong-Wook Han, Ki-Young Moon

Abstract:

The ability to recognize humans and their activities by computer vision is a very important task, with many potential application. Study of human motion analysis is related to several research areas of computer vision such as the motion capture, detection, tracking and segmentation of people. In this paper, we describe a segmentation method for extracting human body contour in modified HLS color space. To estimate a background, the modified HLS color space is proposed, and the background features are estimated by using the HLS color components. Here, the large amount of human dataset, which was collected from DV cameras, is pre-processed. The human body and its contour is successfully extracted from the image sequences.

Keywords: Background Subtraction, Human Silhouette Extraction, HLS Color Space, and Object Segmentation

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1077752

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2080

References:


[1] D. M. Gavrila, "The Visual Analysis of Human Movement: A Survey," Computer Vision and Image Understanding, 73(1), pp.82-98, Jan. 1999.
[2] I. I. Koprinska and S. Carrato, "Temporal Video Segmentation: A Survey," Signal Processing: Image Communication, 16(5), pp.477-500, Jan. 2001.
[3] T. Horprasert, D. Harwood, and L. S. Davis, "A Statistical Approach for Real-Time Robust Background Subtraction and Shadow Detection," in Proceedings of IEEE International Conference on Computer Vision: Frame-Rate Workshop, Kerkyra, Greece, Sep. 1999.
[4] H. Fujiyoshi and A. J. Lipton, "Real-Time Human Motion Analysis by Skeletonization," in Proceedings of IEEE Workshop on Application of Computer Vision, pp.15-21, Princeton, NJ, USA, Oct. 1988.
[5] A. Neri, S. Colonnese, G. Russo, and P. Talone, "Automatic Moving Object and Background Separation," Signal Processing, 66(2), pp.219-232, Apr.1998.
[6] C. Wren, A. Azarbayejani, T. Darrell, and A. Pentland, "Pfinder: Real-Time Tracking of the Human Body," IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(7), pp.780-785, Jul. 1997.
[7] J. D. Shutler, M. G. Grant, M. S. Nixon, and J. N. Carter, "On a Large Sequence-based Human Gait Database," in Proceedings of Recent Advances in Soft Computing, pp.66-71, Nottingham, UK, Dec. 2002.
[8] G. Gordon, T. Darrell, M. Harville, and J. Woodfill, "Background Estimation and Removal based on Range and Color," in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Vol.2, pp.2459-2464, Fort Collins, CO., USA, Jun. 1999.
[9] C. A. Poynton, "Frequently Asked Questions about Color," http://www.poynton.com/notes/colour_and_gamma/ColorFAQ.txt, 1998.
[10] J. D. Foley, A. Van Dam, S. K. Feiner, and J. F. Hughes, Computer Graphics: Principles and Practice, Addition-Wesley, 1990.
[11] T. Q. Chen and Y. Lu, "Color Image Segmentation-An Innovative Approach," Pattern Recognition, 35(2), pp.395-405, Feb. 2002.
[12] J. H. Yoo, D. S. Hwang, K. Y. Moon, and M.S. Nixon, "Automated Human Recognition by Gait using Neural Network," inProceedings of IEEE International Workshops on Image Processing Theory, Tool and Applications, Sousse, pp.362-367, Tunisia, Nov. 2008.