
Proceedings Paper
Hardware-software face detection system based on multi-block local binary patternsFormat | Member Price | Non-Member Price |
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Paper Abstract
Face detection is an important aspect for biometrics, video surveillance and human computer interaction. Due to the complexity of the detection algorithms any face detection system requires a huge amount of computational and memory resources. In this communication an accelerated implementation of MB LBP face detection algorithm targeting low frequency, low memory and low power embedded system is presented. The resulted implementation is time deterministic and uses a customizable AMBA IP hardware accelerator. The IP implements the kernel operations of the MB-LBP algorithm and can be used as universal accelerator for MB LBP based applications. The IP employs 8 parallel MB-LBP feature evaluators cores, uses a deterministic bandwidth, has a low area profile and the power consumption is ~95 mW on a Virtex5 XC5VLX50T. The resulted implementation acceleration gain is between 5 to 8 times, while the hardware MB-LBP feature evaluation gain is between 69 and 139 times.
Paper Details
Date Published: 4 March 2015
PDF: 7 pages
Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 944305 (4 March 2015); doi: 10.1117/12.2178794
Published in SPIE Proceedings Vol. 9443:
Sixth International Conference on Graphic and Image Processing (ICGIP 2014)
Yulin Wang; Xudong Jiang; David Zhang, Editor(s)
PDF: 7 pages
Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 944305 (4 March 2015); doi: 10.1117/12.2178794
Show Author Affiliations
Laurentiu Acasandrei, Instituto de Microelectronica de Sevilla (Spain)
Univ. de Sevilla (Spain)
Univ. de Sevilla (Spain)
Angel Barriga, Instituto de Microelectronica de Sevilla (Spain)
Univ. de Sevilla (Spain)
Univ. de Sevilla (Spain)
Published in SPIE Proceedings Vol. 9443:
Sixth International Conference on Graphic and Image Processing (ICGIP 2014)
Yulin Wang; Xudong Jiang; David Zhang, Editor(s)
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