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《Journal of Computer Research and Development》 2001-10
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ZHOU Zhi Hua ①, HUANG Fu Jie ②, ZHANG Hong Jiang ③, and CHEN Tsuhan ② ①(National Laboratory for Novel Software Technology, Nanjing University, Nanjing 210093) ②(Electrical and Computer Engineering Department, Carnegie Mellon Uni  
When human faces rotate in image depth, even the faces of the same person appear with great variances. In this paper, neural network ensemble is applied to view invariant face recognition. The facial features used are extracted through view specific eigenface analysis. Several neural networks are trained, each for an eigenspace of different views, and their results are combined with another neural network. After the ensemble is trained, view estimation is not required for recognition. Moreover, when new faces are fed, the ensemble will not only give the recognition result but also present an estimated view information. Experimental results show that the recognition accuracy of the proposed approach is better than that of the best individual neural network selected according to the information provided by an accurate front end view estimation process.
【Fund】: 江苏省自然科学基金资助 ( BK2 0 0 14 0 6)
【CateGory Index】: TP183
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