Abstract
In this paper, we present an automatic human portrait system based on the And-Or graph representation. The system can automatically generate a set of life-like portraits in different styles from a frontal face image. The system includes three subsystems, each of which models hair, face and collar respectively. The face subsystem can be further decomposed into face components: eyebrows, eyes, nose, mouth, and face contour. Each component has a number of distinct sub-templates as a leaf-node in the And-Or graph for portrait. The And-Or graph for portrait is like a ”mother template” which produces a large set of valid portrait configurations, which is a ”composite templates” made of a set of sub-templates. Our approach has three novel aspects:(1) we present an And-Or graph for portrait that explains the hierarchical structure and variability of portrait and apply it into practice; (2) we combine hair, face and collar into a system that solves a practical problem; (3) The system can simultaneously generate a set of impressive portraits in different styles. Experimental results demonstrate the effectiveness and life-likeness of our approach.
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Min, F., Suo, JL., Zhu, SC., Sang, N. (2007). An Automatic Portrait System Based on And-Or Graph Representation. In: Yuille, A.L., Zhu, SC., Cremers, D., Wang, Y. (eds) Energy Minimization Methods in Computer Vision and Pattern Recognition. EMMCVPR 2007. Lecture Notes in Computer Science, vol 4679. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74198-5_15
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DOI: https://doi.org/10.1007/978-3-540-74198-5_15
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