Composite Templates for Cloth Modeling and Sketching

Cloth modeling and recognition is an important and challenging problem in both vision and graphics tasks, such as dressed human recognition and tracking, human sketch and portrait. In this paper, we present a context sensitive grammar in an And-Or graph representation which will produce a large set of composite graphical templates to account for the wide variabilities of cloth configurations, such as T-shirts, jackets, etc. In a supervised learning phase, we ask an artist to draw sketches on a set of dressed people, and we decompose the sketches into categories of cloth and body components: collars, shoulders, cuff, hands, pants, shoes etc. Each component has a number of distinct subtemplates (sub-graphs). These sub-templates serve as leafnodes in a big And-Or graph where an And-node represents a decomposition of the graph into sub-configurations with Markov relations for context and constraints (soft or hard), and an Or-node is a switch for choosing one out of a set of alternative An...

• Type: Conference
• Year: 2006
• Where: CVPR
• Authors: Hong Chen, Zijian Xu, Ziqiang Liu, Song Chun Zhu
• Keywords: And-or Graph Representation, Big And-or Graph, Composite Cloth Template, Computer Vision, Context Free Grammar, Context Sensitive Grammar, CVPR 2006