Abstract

Pedestrian is a main part of the road system.To detect pedestrian is a critical thing in a computer vision .There are many methods are available to detect pedestrian and subsequently to take some action.In this review based paper we have discussed some popular techniques.

References

• D. Geronimo, A.M. Lopez, A.D. Sappa, and T. Graf, “Survey on Pedestrian Detection for Advanced Driver Assistance Systems,”IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 32, no. 7, pp. 1239-1258, July 2010
• M. Enzweiler and D.M. Gavrila, “Monocular PedestrianDetection: Survey and Experiments,” IEEE Trans. PatternAnalysis and Machine Intelligence, vol. 31, no. 12, pp. 2179-2195, Dec. 2009.
• N. Dalal and B. Triggs, “Histograms of Oriented Gradients for Human Detection,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2005.
• D. Martin, C. Fowlkes, and J. Malik, “Learning to Detect Natural Image Boundaries Using Local Brightness, Color, and Texture Cues,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 26, no. 5, pp. 530-549, May 2004.
• D. Scharstein and R. Szeliski, “A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms,” Int’l J. Computer Vision, vol. 47, pp. 7-42, 2002.
• E. Seemann, M. Fritz, and B. Schiele, “Towards Robust Pedestrian Detection in Crowded Image Sequences,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2007
• M. Hussein, F. Porikli, and L. Davis, “A ComprehensiveEvaluation Framework and a Comparative Study for HumanDetectors,” IEEE Trans. Intelligent Transportation Systems, vol. 10,no. 3, pp. 417-427, Sept. 2009.
• T. Ojala, M. Pietik¨ainen, and D. Harwood. A comparativestudy of texture measures with classification based on featured distributions. Pattern Recognition, 29(1):51–59, 1996
• C.H. Lampert, M.B. Blaschko, and T. Hofmann, “Beyond Sliding Windows: Object Localization by Effcient subwindow Search,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2008.
• T. Moeslund, A. Hilton, and V. Kru¨ ger, “A Survey of Advances in Vision-Based Human Motion Capture and Analysis,” Computer Vision and Image Understanding, vol. 104, nos. 2/3, pp. 90-126, 2006
• T. Gandhi and M.M. Trived, “Pedestrian Protection Systems:Issues, Survey, and Challenges,” IEEE Trans. Intelligent Transportation Systems, vol. 8, no. 3, pp. 413-430, Sept. 2007.
• M. Bertozzi, A. Broggi, R. Chapuis, F. Chausse, A. Fascioli, and A.Tibaldi, “Shape-Based Pedestrian Detection and Localization,”Proc. IEEE Int’l Conf. Intelligent Transportation Systems, pp. 328-333,2003.
• Wentao Yao, Zhidong Deng” A Robust Pedestrian Detection Approach Based on Shapelet Feature and Haar Detector Ensembles” Tsinghua Science and Technology Volume 17, Number 1, February 2012 llpp40-50
• Pawan Sinha,Tomaso A.Poggio “Pedestrian detection using wavelet templates”Processing /CVRR,iee computer society conference on computer vision and pattern recognition.-1977
• Shuoping Wang, Zhike Han, Li Zhu and Qi Chen,” A Novel Approach to Design the Fast Pedestrian Detection for Video Surveillance System” International Journal of Security and Its Applications Vol.8, No.1 (2014), pp.93-102
• K. Fukushima, S. Miyake, and T. Ito, “Neocognitron: A Neural Network Model for a Mechanism of Visual Pattern Recognition,”IEEE Trans. Systems, Man, and Cybernetics, vol. 13, pp. 826-834,1983
• P. Viola, M. Jones, and D. Snow, “Detecting Pedestrians Using Patterns of Motion and Appearance,” Int’l J. Computer Vision, vol. 63, no. 2, pp. 153-161, 2005