Paper
27 February 2015 Embedded wavelet-based face recognition under variable position
Pascal Cotret, Stéphane Chevobbe, Mehdi Darouich
Author Affiliations +
Proceedings Volume 9400, Real-Time Image and Video Processing 2015; 94000A (2015) https://doi.org/10.1117/12.2083046
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States
Abstract
For several years, face recognition has been a hot topic in the image processing field: this technique is applied in several domains such as CCTV, electronic devices delocking and so on. In this context, this work studies the efficiency of a wavelet-based face recognition method in terms of subject position robustness and performance on various systems. The use of wavelet transform has a limited impact on the position robustness of PCA-based face recognition. This work shows, for a well-known database (Yale face database B*), that subject position in a 3D space can vary up to 10% of the original ROI size without decreasing recognition rates. Face recognition is performed on approximation coefficients of the image wavelet transform: results are still satisfying after 3 levels of decomposition. Furthermore, face database size can be divided by a factor 64 (22K with K = 3). In the context of ultra-embedded vision systems, memory footprint is one of the key points to be addressed; that is the reason why compression techniques such as wavelet transform are interesting. Furthermore, it leads to a low-complexity face detection stage compliant with limited computation resources available on such systems. The approach described in this work is tested on three platforms from a standard x86-based computer towards nanocomputers such as RaspberryPi and SECO boards. For K = 3 and a database with 40 faces, the execution mean time for one frame is 0.64 ms on a x86-based computer, 9 ms on a SECO board and 26 ms on a RaspberryPi (B model).
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Pascal Cotret, Stéphane Chevobbe, and Mehdi Darouich "Embedded wavelet-based face recognition under variable position", Proc. SPIE 9400, Real-Time Image and Video Processing 2015, 94000A (27 February 2015); https://doi.org/10.1117/12.2083046
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Cited by 1 scholarly publication.
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KEYWORDS
Databases

Facial recognition systems

Tin

Wavelets

Discrete wavelet transforms

Wavelet transforms

Tolerancing

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