Robust Face Recognition using Minimax Probability Machine
Face recognition has been widely explored. Many techniques have been applied in various applications. Robustness and reliability become more and more important for these applications especially, in security systems. A new face recognition approach is proposed based on a state-of-the-art classificati...
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| Main Authors: | , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2004
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/2400 http://dx.doi.org/10.1109/ICME.2004.1394428 |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | Face recognition has been widely explored. Many techniques have been applied in various applications. Robustness and reliability become more and more important for these applications especially, in security systems. A new face recognition approach is proposed based on a state-of-the-art classification technique called minimax probability machine (MPM). Engaging the binary MPM technique, we present a multi-class MPM classification for robust face recognition. In experiments, we compare our MPM-based face recognition algorithm with traditional techniques, including neural network and support vector machine. The experimental results show that the MPM-based face recognition technique is competitive and promising for robust face recognition |
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