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GPU Accelerated Face Recognition system with Enhanced Local Ternary Patterns using OpenCL

Vinith, B and Akhila, MK and Naik, Narmada and Rathna, GN (2015) GPU Accelerated Face Recognition system with Enhanced Local Ternary Patterns using OpenCL. In: International Conference on Digital Image Computing: Techniques and Applications, NOV 23-25, 2015, Adelaide, AUSTRALIA, pp. 366-372.

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Official URL: http://dx.doi.org/10.1109/DICTA.2015.7371263


Enhanced Local Ternary Patterns (ELTP) significantly improves performance over other feature descriptor methods including Local Binary Patterns (LBP) and Local Ternary Patterns (LTP). Sequential implementation of ELTP results in poor performance in terms of execution time for real time systems. Speed and accuracy are important characteristics of a real time face recognition system. With the aim of fulfilling both these criteria, this paper presents an implementation of GPU Accelerated Face Recognition System with ELTP using OpenCL framework. As a result of our Optimization techniques, we have achieved highest kernel execution speedup of 374x for ELTP image and histogram generation with 4096 x H 4096 (16MP) image resolution when it is implemented on GPU. Face recognition with ELTP showed higher recognition rates on ORL database. We also implemented LBP and LTP algorithms on GPU and compared their performances with ELTP. Similar Optimization techniques were applied for LBP kernel executions, which resulted in much higher speedups when compared to their previous implementations. Experimental results demonstrated that Parallel implementation with ELTP on GPU (AMD Radeon HD 7650M) outperforms CPU based face recognition system using LBP in terms of speed and accuracy.

Item Type: Conference Proceedings
Additional Information: Copy right for this article belongs to the IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 03 Dec 2016 09:59
Last Modified: 03 Dec 2016 09:59
URI: http://eprints.iisc.ac.in/id/eprint/55386

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