Face recognition via a projective compressive sensing system
| Autor: | Charlie J. Keith, Randy R. Reibel, Peter A. Roos, Brant M. Kaylor |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
Engineering
Pixel business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Photodetector Facial recognition system Digital micromirror device law.invention Compressed sensing law Compression (functional analysis) Face (geometry) Pattern recognition (psychology) Computer vision Artificial intelligence business |
| Zdroj: | SPIE Proceedings. |
| ISSN: | 0277-786X |
| DOI: | 10.1117/12.909056 |
| Popis: | A projective compressive sensing system for face recognition is presented. The Fisherfaces method was utilized for classification of the face images. The system uses a digital micromirror device to project measurement vectors onto the scene and a single photodetector to collect the backscattered illumination. Experimentally, the system accuracy was 95.5% using only 32 measurements per image; this performance matches the simulation results. The total number of image pixels was 5,736 (84 × 64) resulting in a compression factor of 168 over a conventional imaging system. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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