Fast People Counting Using Head Detection from Skeleton Graph

In this paper, we present a new method for counting people.This method is based on the head detection after asegmentation of the human body by skeleton graph process.The skeleton silhouette is computed and decomposed into aset of segments corresponding to the head , torso and limbs.This structure captures the minimal information about theskeleton shape. No assumption is made about the viewpoint,this is done after the head pose process. Several resultspresent the efficiency of the labelling process , particularlyits structural properties for the detection of heads within acrowd. A proposed method has been tested with an experimentof counting the number of pedestrians passing in aspecific area.

[1]  Gregory D. Hager,et al.  Fast and Globally Convergent Pose Estimation from Video Images , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Jean-Philippe Thiran,et al.  Counting Pedestrians in Video Sequences Using Trajectory Clustering , 2006, IEEE Transactions on Circuits and Systems for Video Technology.

[3]  Jaihie Kim,et al.  An Area-Based Decision Rule for People-Counting Systems , 2006, MRCS.

[4]  Jitendra Malik,et al.  Estimating Human Body Configurations Using Shape Context Matching , 2002, ECCV.

[5]  Hai Tao,et al.  Counting Pedestrians in Crowds Using Viewpoint Invariant Training , 2005, BMVC.

[6]  W. Eric L. Grimson,et al.  Learning Patterns of Activity Using Real-Time Tracking , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Nuno Vasconcelos,et al.  Privacy preserving crowd monitoring: Counting people without people models or tracking , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[8]  Larry S. Davis,et al.  Ghost: a human body part labeling system using silhouettes , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[9]  Ralph Roskies,et al.  Fourier Descriptors for Plane Closed Curves , 1972, IEEE Transactions on Computers.

[10]  Nicolas Thome,et al.  Human Body Part Labeling and Tracking Using Graph Matching Theory , 2006, 2006 IEEE International Conference on Video and Signal Based Surveillance.

[11]  Paul A. Viola,et al.  Detecting Pedestrians Using Patterns of Motion and Appearance , 2005, International Journal of Computer Vision.

[12]  David G. Lowe,et al.  Fitting Parameterized Three-Dimensional Models to Images , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Yongtae Do.  Region Based Detection of Occluded People for the Tracking in Video Image Sequences , 2005, CAIP.

[14]  Ramakant Nevatia,et al.  Bayesian human segmentation in crowded situations , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[15]  King-Sun Fu,et al.  Shape Discrimination Using Fourier Descriptors , 1977, IEEE Transactions on Pattern Analysis and Machine Intelligence.