Commenced in January 2007
Paper Count: 30184
Human Verification in a Video Surveillance System Using Statistical Features
Authors: Sanpachai Huvanandana
Abstract:A human verification system is presented in this paper. The system consists of several steps: background subtraction, thresholding, line connection, region growing, morphlogy, star skelatonization, feature extraction, feature matching, and decision making. The proposed system combines an advantage of star skeletonization and simple statistic features. A correlation matching and probability voting have been used for verification, followed by a logical operation in a decision making stage. The proposed system uses small number of features and the system reliability is convincing.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1058445Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1132
 Akira U. and Nobuji T., "Human Detection using Geometrical Pixel Value Structure", IEEE Internation Conference on Automatic Face and Gesture Recognition, FGR-02, 2002.
 Borghys, D. , Verlinde, P., Perneel, C. , Acheroy, M. , "Multi-level Data Fusion for the Detection of Targets using Multi-Spectral Image Sequences", Opt. Eng., Vol. 37, No. 2, pp. 477-484, February 1998.
[3a] Chen X, He Z, Anderson D, Keller J & Skubic M, "Adaptive Silhouette Extraction and Human Tracking in Complex and Dynamic Environments", International Conference on Image Processing, Atlanta, Georgia, October 8-13, 2006.
 Constantine P., Theodoros E., and Tomaso P., "A trainable pedestrian detection system", In Proc. of Intelliggent Vehicles, pages 241-246, 1998.
 Elgammal A., Harwood D., and Davis L.S., "Non-Parametric Model for Background Subtraction.", International Proc. IEEE ICCV-99 Frame- Rate Workshop, 1999.
 Fengliang Xu, Kikuo Fujimura," Human Detection Using Depth and Gray Images.",IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS- 03 ), 2003.
 Grimson W. E. L. and Stauffer C., "Adaptive Background Mixture Models for Real-time Tracking.", Proc. IEEE Conference CVPR, Vol. 1 ,pp.22-29, 1999.
 Haritaoglu I., Harwood D., and Davis L.S., "W4: Real-Time System for Detection and Tracking People in 2 ┬¢ D.", 5th European Conference on Computer Vision, 1998.
 Hironobu Fujiyoshi and Alan J. Lipton, "Real-time Human Motion Ananlysis by Image Skeletonization", IEICE Transanction on Information & System, vol.E87-D, No.1, 2004.
 Jianpeng Z. and Jack H., "Real Time Robust Human Detection and Tracking System", Proceeding of 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition workshop (CVPR-05), Vol.3.
 Oliver N., B. Rosario, and A. Pentland, "A Baysian Computer Vision System for Modeling Human Interactions.", International Conference on Vision System, 1999.
 Rafael C. Gonzalez and Richard E. Woods, "Digital Image Processing", Prentice Hall, 2002.
 Rosin, P.L. , Ellis, T. , "Image Difference Threshold Strategies and Shadow Detection", British Machine Vision Conf., pp. 347-356, 1995.
 Wren C.R., Azarbayejani A., Darrell T., and Pentland A., "Pfinder: Realtime Tracking of Human Body.", IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 19, No.7, pp.780-785, July 1997.
 Wu B. and Nevatia R, "Detection of Multiple, Partially Occluded Humans in a Single Image by Basian Combination of Edgelet Part Detectors" ICCV-05, 2005.