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Face detection and recognition with multiple appearance models for mobile robot application

For visual navigation, mobile robot can use a stereo camera which has large field of view. In this paper, we propose an algorithm to detect and recognize human face on the basis of such camera system. In this paper, a new ‘coarse to fine’ detection algorithm is proposed. For coarse detection, nearly face-like areas are found in entire image using dual ellipse templates. And, detailed alignment of facial outline and features is performed on the basis of viewbased multiple appearance model. Because it’s hard to finely align with facial features in this case, we try to find most resembled face image area is selected from multiple face appearances using most distinguished facial featurestwo eyes. In face recognition step, probabilistic density of above image is estimated from a view of maximum-likelihood. Multi-modal Gaussian densities from expectation-maximization algorithm is applied and multiple appearance model of person is also used, which can cope with limitations such as a variety of training samples, varying illumination conditions. Finally, we experiment with these methods within the traveling range of mobile robot and results of face detection and recognition are reported.