疎な距離情報と形状モデルとの階層的照合による2次元物体の認識

抄録

In this paper, we discuss a matching method of objects from range data measured more sparsely than the size of object's local structure. In such a case, observed data differ from models in several reasons; 1) occlusion of hollow part, 2) omission of feature elements, 3) bluntness of edges, 4) isolation of observed points, and 5) inconsistency with general knowledges. The aim of the paper is to develop a way to compare sparse imcomplete data with complete model description in hierarchical manner using strip tree, and the validity of the algorithm is demonstrated for 2-D examples. We also discuss 3-D matching of depth images by extending strip tree.