Abstract
Different biometrics traits are in use nowadays with different accuracy. Gait biometrics is getting popularity among the researchers due to its capability to recognize the people even without cooperation of subject. However, the problems such as shadow detection and shadow removal of moving subjects in visual surveillance, less number of images in different conditions, and the data which is recorded from surveillance cameras consist of multiple views. This paper presents three algorithms, to remove shadows at the time of silhouette generation from the recorded video, synthetic GEI templates generation to enhance the corresponding gallery probes dataset, and singular value decomposition transformation algorithm to transform the gait feature from one view to another view. Experimental results on a benchmark suite of indoor and outdoor video sequences show that the performance of proposed algorithms is better than the other existing algorithms.
The original version of this chapter was revised: For detailed information please see correction The correction to this chapter is available at https://doi.org/10.1007/978-81-322-0491-6_98
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Katiyar, R., Arya, K.V., Pathak, V.K. (2012). RETRACTED CHAPTER: Multiview Gait Recognition Based on Silhouettes Generated after Shadow Detection and Removal Using Photometric Properties Method. In: Deep, K., Nagar, A., Pant, M., Bansal, J. (eds) Proceedings of the International Conference on Soft Computing for Problem Solving (SocProS 2011) December 20-22, 2011. Advances in Intelligent and Soft Computing, vol 131. Springer, New Delhi. https://doi.org/10.1007/978-81-322-0491-6_36
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DOI: https://doi.org/10.1007/978-81-322-0491-6_36
Publisher Name: Springer, New Delhi
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