Title :
Robust face recognition using minimax probability machine
Author :
Hoi, Chu-Hong ; Lyu, Michael R.
Author_Institution :
Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong
Abstract :
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
Keywords :
face recognition; image classification; minimax techniques; probability; classification technique; minimax probability machine; neural network; reliability; robust face recognition; security systems; support vector machine; Application software; Computer science; Face recognition; Minimax techniques; Neural networks; Principal component analysis; Reliability engineering; Robustness; Support vector machine classification; Support vector machines;
Conference_Titel :
Multimedia and Expo, 2004. ICME '04. 2004 IEEE International Conference on
Conference_Location :
Taipei
Print_ISBN :
0-7803-8603-5
DOI :
10.1109/ICME.2004.1394428