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A Novel Equation based Classifier for Detecting Human in Images

by Subra Mukherjee, Karen Das
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 72 - Number 6
Year of Publication: 2013
Authors: Subra Mukherjee, Karen Das
10.5120/12496-7272

Subra Mukherjee, Karen Das . A Novel Equation based Classifier for Detecting Human in Images. International Journal of Computer Applications. 72, 6 ( June 2013), 9-16. DOI=10.5120/12496-7272

@article{ 10.5120/12496-7272,
author = { Subra Mukherjee, Karen Das },
title = { A Novel Equation based Classifier for Detecting Human in Images },
journal = { International Journal of Computer Applications },
issue_date = { June 2013 },
volume = { 72 },
number = { 6 },
month = { June },
year = { 2013 },
issn = { 0975-8887 },
pages = { 9-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume72/number6/12496-7272/ },
doi = { 10.5120/12496-7272 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:37:12.029895+05:30
%A Subra Mukherjee
%A Karen Das
%T A Novel Equation based Classifier for Detecting Human in Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 72
%N 6
%P 9-16
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Shape based classification is one of the most challenging tasks in the field of computer vision. Shapes play a vital role in object recognition. The basic shapes in an image can occur in varying scale, position and orientation. And specially when detecting human, the task becomes more challenging owing to the largely varying size, shape, posture and clothing of human. So, in our work we detect human, based on the head-shoulder shape as it is the most unvarying part of human body. Here, firstly a new and a novel equation named as the "Omega Equation" that describes the shape of human head-shoulder is developed and based on this equation, a classifier is designed particularly for detecting human presence in a scene. The classifier detects human by analyzing some of the discriminative features of the values of the parameters obtained from the Omega equation. The proposed method has been tested on a variety of shape dataset taking into consideration the complexities of human head-shoulder shape. In all the experiments the proposed method demonstrated satisfactory results.

References
  1. Liang Wang, Weiming Hu, Tieniu Tan, "Recent developments in human motion analysis"-Journal of pattern recognition Society,vol. 36, pp-585-601, 2003. .
  2. Anuj Mohan, Constantine Papageorgiou, and Tomaso Poggio, "Example-Based Object Detection in Images by Components", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, no. 4, APRIL 2001.
  3. Tudor Barbu, "Novel Approach for Moving Human Detection and Tracking in Static Camera Video Sequences", Proceedings of the Romanian Academy, Series A, Volume 13, Number 3/2012, pp. 269–277.
  4. P. S. Hiremath and Jagadeesh Pujari, "Content Based Image Retrieval using Color, Texture and Shape features", Proceedings of the 15th International Conference on Advanced Computing and Communications, 2007 IEEE computer Society.
  5. Kart-Leong Lim, Hamed Kiani Galoogahi, "Shape Classification Using Local and Global Features" proceedings of Fourth Pacific-Rim Symposium on Image and Video Technology, 2010.
  6. Haibin Ling, David W. Jacobs, "Shape Classification Using the Inner-Distance"- IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, NO. 2, 2007.
  7. Stanley Bileschi, Lior Wolf, "Image representations beyond histograms of gradients: The role of Gestalt descriptors", Proceedings of IEEE conference on Computer Vision and Pattern recognition, 2007.
  8. Xiang Bai Wenyu Liu Zhuowen Tu, "Integrating Contour and Skeleton for Shape Classification", proceedings of 12th IEEE International conference on Computer Workshops (ICCV), 2009.
  9. Longbin Chen, Julian J. Mc Auley, Rogerio S. Feris, Tib´erio S. Caetano, Matthew Turk, "Shape Classification Through Structured Learning of Matching Measures", Proceedings of IEEE conference on Computer Vision and Pattern Recognition (CVPR), 2009.
  10. Dengsheng Zhang, Guojun Lu, "Review of shape representation and description techniques"- Journal of the pattern Recognition Society, Elsevier, Vol. 37, Issue-1, 2004.
  11. Kang B. Sun and Boaz J. Super, "Classification of Contour Shapes Using Class Segment Sets", Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2005.
  12. Hien Van Nguyen, Fatih Porikli, "Support Vector Shape: A Classifier Based Shape Representation", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 35, Issue 4, pp-970-982.
  13. Zhe Lin and Larry S. Davis, "Shape-Based Human Detection and Segmentation via Hierarchical Part-Template Matching", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, No. 4,pp-604-618, 2010.
  14. William Robson Schwartz, Aniruddha Kembhavi, David Harwood, Larry S. Davis, "Human Detection Using Partial Least Squares Analysis", proceedings of IEEE 12th International Conference on Computer Vision,pp-24-31, 2009.
  15. Yanjiang wang, Baozong Yuan, "A novel approach for Human Face detection from color images under Complex Background"- Pattern Recognition, Elsevier, Volume 34, issue 10, pp- 1983-1992, 2010.
  16. Krystian Mikolajczyk, Cordelia Schmid, Andrew Zisserman, "Human Detection based on a Probabilistic Assembly of Robust Part Detector", Proceedings of 8th European Conference on Computer Vision (ECCV),pp-68-82, 2004.
  17. Bo Wu and Ram Nevatia "Detection and Tracking of Multiple, Partially Occluded Humans by Bayesian Combination of Edgelet based Part Detectors"- International Journal of Computer Vision (Springer),Vol. 75, Issue. 2,pp-247-266, 2007.
  18. Huazhong Xu, Pei Lv, Lei Meng, "A People Counting System based on Head-shoulder Detection and Tracking in Surveillance Video", Proceedings of International Conference On Computer Design And Applications (ICCDA), 2010.
  19. Jorge Garc?a, Alfredo Gardel, Ignacio Bravo, Jos´e Luis L´azaro, Miguel Mart´?nez and David Rodr´?guez, " Directional People Counter based on Heads Tracking", IEEE transaction on Industrial Electronics, Vol. PP, Issue:99,2012.
  20. Liu Dong Xi Lin, "Monocular-Vision-Based Study on Moving Object Detection and Tracking", Proceedings of 4th International Conference on New Trends in Information Science and Service Science (NISS), 2010.
  21. Subra Mukherjee, Karen Das, "An Adaptive GMM Approach To Background Subtraction for Application in Real Time Surveillance", International Journal of Research in Engineering and Technology, vol. 2, Issue 1, pp-25-29.
Index Terms

Computer Science
Information Sciences

Keywords

Omega Equation Classifier Human Detection Omega Shape Gaussian Mixture Model