3-D Data Acquisition of Scene by Motion Vision and its Understanding by Spatial Reasoning

点击翻译按钮获取中文摘要

It is one of central problems of computer vision to understand the spatial structure of scene by interpreting images taken at various viewpoints.In order to interpret those images coherently, it is important to establish correspondences of features among the images. We have found strong geometrical constraints to establish correspondences of features for three camera stereo which we call as trinocular constraints.In this study, we have extended the trinocular constraints so that they can also be applied to motion vision. We have utilized edge-segments as units for correspondences. When the correspondences have been established, we obtain the 3-D coordinates of the edge-segments by using the triangulatin principle and make the 3-D model of the scene. This model is, however,a kind of wire-framed model where only the 3-D coordinates of edge-segments are known. From this wire-frame model, we next extract surfaces and recognize spatial structure of the scene by analyzing relations of these surfaces. Here, we took knowledge-based approach in which knowledge base contains rules which hold generally in the 3-D world.