Taking advantage of image-based and geometry-based constraints to recover 3-D surfaces

被引:18
作者
Fua, P
Leclerc, YG
机构
[1] SRI International, Menlo Park, CA 94025
关键词
D O I
10.1006/cviu.1996.0048
中图分类号
TP18 [人工智能理论];
学科分类号
081104 [模式识别与智能系统]; 0812 [计算机科学与技术]; 0835 [软件工程]; 1405 [智能科学与技术];
摘要
A unified framework for 3-D shape reconstruction allows us to combine image-based and geometry-based information sources. The image information is akin to stereo and shape-from-shading, while the geometric information may be provided in the form of 3-D points, 3-D features, or 2-D silhouettes. A formal integration framework is critical in recovering complicated surfaces because the information from a single source is often insufficient to provide a unique answer. Our approach to shape recovery is to deform a generic object-centered 3-D representation of the surface so as to minimize an objective function, This objective function is a weighted sum of the contributions of the various information sources. We describe these various terms individually, our weighting scheme, and our optimization method, Finally, we present results on a number of difficult images of real scenes for which a single source of information would have proved insufficient. (C) 1996 Academic Press, Inc.
引用
收藏
页码:111 / 127
页数:17
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