Robust frontal view search using extended manifold learning
Journal of Visual Communication and Image Representation
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We have constructed a simple and fast system to detect frontal human faces in complex environment. There are two main contributions of our work: 1) We use a fast image segmentation method based on connected components labelling to select candidate face areas. 2) We propose a positive-negative attractor template to examine face areas. A valley detector is used to search the valley-like points of eyes and mouths. We test the system on images in complex environment and with confusing objects. The experiment shows a robust detection result with few false detected faces.