COMPOSITE SKETCH SHAPE RECOGNITION BASED ON DAGSVM AND DECISION TREE

摘要：

Sketch recognition provides the basis for semantic processing in Sketching Understanding, and it consists of two sequential and cyclic phases: primitive shape recognition and composite shape recognition. In this paper, a composite shape recognition algorithm based on Support Vector Machines (SVM) and Decision Tree is proposed. Directed Acyclic Graphs SVM (DAGSVM) is used for primitive shape recognition and composite shape recognition. The decision tree is introduced to pre-classify the composite shape and to reduce the computational cost of recognition. The algorithm integrates the advantages of feature-based and similarity-based recognition approaches, and can deal with sketching sequence properly. Experiment demonstrates that the model is feasible.

关键词： Sketch Recognition Composite shape recognition Spatial constraints Directed Acyclic Graphs SVM (DAGSVM) Decision Tree

作者: SHI-ZHONG LIAO WEN-GANG LIU WEI GUO

作者单位: School of Computer Science and Technology, Tianjin University, Tianjin 300072, China

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 3254-3259

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）