OBJECT RECOGNITION USING A TREE-LIKE PROCEDURE GENERATED FROM 3-D MODEL
Yasukazu Okamoto, Yoshinori Kuno, Kazunori Onoguchi, Mutsumi Watanabe, Haruo Asada · 1988
This paper presents a vision system which automatically generates an object recognition procedure from a 3-D model, and recognizes the object by executing this procedure. The change in object appearances due to the viewpoint is a main issue in 3-D model vision. In this system, the appearances of an object from various view points are described with visible 2-D figures, such as parallel lines and ellipses. These figures are projections of linear or circular visible elements in the model. Then, the appearance descriptions are compared. Similar figures are extracted and merged into a new description, which represents a common and general appearance of the old ones. This process is iterated and ends in a tree-like procedure. The system search the procedure tree and recognizes the object. At a visited node of the tree, figure is estimated by the recognition procedure and looked for in the image. If such figures are detected, a child of the current node is selected for the next visit. Detected figures are used for estimation at the next node. The number of object candidates increases as the number of detected figures increases, and propagated candidates construct a tree. The system searches the candidate tree in addition to the procedure tree. Experimental results show the efficiency of proposed system.