期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2004
卷号：XXXV Part B5
页码：105-109
出版社：Copernicus Publications
摘要：For measuring complex industrial objects using vision metrology systems, automatic optimum network design is a real challenge. In the absence of given or simulated 3D CAD models of the objects and the workspace, the complexity of objects introduces several uncertainty factors into the camera placement decision making process. These uncertainty factors include the vision constraints such as visibility, accessibility and camera-object distance. For more complex objects, visibility is vastly influenced by hidden areas, the incidence angle of a target and the camera orientation. Mutual dependency of these factors increases the difficulty of camera placement. Further these factors directly influence the mensuration quality, in particular, precision and reliability. If an a priori 3D CAD model of the object is available, the aforementioned ambiguities can be tackled. However, a 3D model is often not available which makes the camera placement problem a nondeterministic process. An answer to this problem is to develop a fuzzy logic inference approach for camera placement and network design. The idea is to deal with the vision constraints in a fuzzy manner. In this paper a novel method based on fuzzy logic reasoning strategy is proposed for the camera placement. The system is designed to make use of human type reasoning strategy by incorporating appropriate rules.The paper reports on the results achieved by testing the fuzzy based camera placement approach on simulated and real objects. The results indicate that this new conceptual approach has a remarkable strength for automatic sensor placement in vision metrology
