Browse > Article
http://dx.doi.org/10.5909/JBE.2012.17.4.611

User Detection and Main Body Parts Estimation using Inaccurate Depth Information and 2D Motion Information  

Lee, Jae-Won (Division of electronic computer Engineering, Chonnam National Univ.)
Hong, Sung-Hoon (School of Electronic & Computer Engineering, Chonnam National Univ., Information & Telecommunication Research Institute)
Publication Information
Journal of Broadcast Engineering / v.17, no.4, 2012 , pp. 611-624 More about this Journal
Abstract
'Gesture' is the most intuitive means of communication except the voice. Therefore, there are many researches for method that controls computer using gesture input to replace the keyboard or mouse. In these researches, the method of user detection and main body parts estimation is one of the very important process. in this paper, we propose user objects detection and main body parts estimation method on inaccurate depth information for pose estimation. we present user detection method using 2D and 3D depth information, so this method robust to changes in lighting and noise and 2D signal processing 1D signals, so mainly suitable for real-time and using the previous object information, so more accurate and robust. Also, we present main body parts estimation method using 2D contour information, 3D depth information, and tracking. The result of an experiment, proposed user detection method is more robust than only using 2D information method and exactly detect object on inaccurate depth information. Also, proposed main body parts estimation method overcome the disadvantage that can't detect main body parts in occlusion area only using 2D contour information and sensitive to changes in illumination or environment using color information.
Keywords
Depth Information; Object Detection; Body Parts Estimation;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Comaniciu D, Meer P, "Mean shift: a robust appoach toward feature space analysis," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol, No, pp.603-619, 2002
2 Shao-Yi Chien, Yu-Wen Huang, Bing-Yu Hsieh, Shyh-Yih Ma, Liang-Gee Chen, "Fast video segmentation algorithm with shadow cancellation, global motion compensation, and adaptive threshold techniques," Multimedia, IEEE Transaction on, Vol.6, No.5, pp.732-748, Oct.2004.   DOI   ScienceOn
3 Chia-Feng Juang, Chia-Ming Chang, Jiuh-Rou Rou, Lee D, "Computer vision-based human body Segmentation and posture estimation", Systems, Man and Cybernetics, Part A, Systems and Humans, IEEE Transactions on, Vol.39, No.1, pp.119-133, Jan.2009   DOI   ScienceOn
4 Stella X. Yu, R. Gross and J. Shi, "Concurrent object recognition and segmentation by graph partitioning", Proc. Neural Information Processing Systems(NIPS'02), pp.1383-1390.
5 Ismail Haritaoglu. David Harwood, Larry S. Davis, "W4S: A Real-Time System for Detecting and Tracking People in 2.5D", ECCV'98 In Computer Vision, Vol, No, pp., 1998
6 Parvizi. E, Wu, Q.M.J, "Multiple Object Tracking Based on Adaptive Depth Segmentaion", Computer and Robot Vision 2008, Canadian Conference on, Vol, No, pp.273-277, May.2008
7 Yinghua Shen, Chaohui Lu, Pin Xu, "Stereoscopic Video Object Segmentation Based on Disparity Map", Measuring Technology and Mechatronics Automation 2010, Vol.3, No, pp.493-495, March.2010
8 Boykov, Y, Kolmogorov. V, "An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimiztion in Vision", IEEE Transactions on PAMI, Vol.26, No9, pp.1124-1137, 2004   DOI   ScienceOn
9 Fujiyoshi. H, Lipton A.J, "Real-time human motion analysis by image skeletonization" Applications of Computer Vision, 1998, WACV98, Proceedings, Fourth IEEE Workshop on, Vol., No., pp.15-21, Oct.1998
10 Haritaoglu. I, Harwood. D, Davis L.S, "Ghost : a human body part labeling system using silhouettes", Pattern Recognition, 1998.Proceedings, Fourteenth International Conference on, Vol.1, No., pp.77-82, Aug.1998
11 Sangho Park, J.K. Aggarwal, "Segmentation and Tracking of Interacting Human Body Parts under Occlusion and Shadowing", Proc. Motion and Video Computing(MOTION'02), pp.105-111, Dec.2002.
12 Kikuo Jujimura, Touding Zhu, Victor Ng-Thow-Hing, "Estimating Pose from Depth Image Stream", IEEE International Conference on Humanoid Robots 2005, pp.154-160, 2005.
13 Haritaoglu. I, Harwood. D, Davis. L.S, "W4 : Who? When? Where? What? A Real Time System for Detecting and Tracking People", Automatic Face and Gesture Recognition,1998.IEEE, Vol, No, pp.222-227, Aug.2000
14 Y. Ma, S. Worrall, A.M. Kondoz, "Automatic video object segmentation using depth information and an active contour model," Multimedia Signal Processing, 2008 IEEE 10th Workshop on, pp.910-914, Oct.2008.
15 C. Stauffer and W.E.L. Grimson, "Adaptive background mixture models for real-time tracking" Proc. IEEE Int Conf. on Computer Vision and Pattern Recognition, pp.246-252, 1999.
16 Haritaoglu. I, Harwood. D, Davis. L.S, "W4 : Real-time Surveillance of people and their activities", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.22, No.8, Aug.2000