Face Detection using Half-Face Templates

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Face detection is the first important step in many face image processing applications. Although a lot of work has been done on detecting frontal faces much less effort has been put into detecting faces with large image-plane or depth rotations. Most templates used in face detection are whole-face templates. However, such templates are ineffective for faces significantly rotated in depth. We propose to use half-face templates to detect faces with large depth rotations. Our experimental results show that half-face templates significantly outperform whole-face templates in detecting faces having large out-plane rotations and performs as well as whole-face templates in detecting frontal faces.

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Indiana University Computer Science Technical Reports; TR572

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