PCA, Neural Networks and Estimation for Face Detection
A generative neural network model, constrained by non-face examples chosen by an iterative algorithm, is applied to face detection. To extend the detection ability in orientation and to decrease the number of false alarms, different combinations of networks are tested: ensemble, conditional ensemble and conditional mixture of networks. The use of a conditional mixture of networks obtains better results on different benchmark face databases than state-of-the-art.
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