Department of Computer Science, Australian National University, Canberra, Australia.
IEEE Trans Pattern Anal Mach Intell. 1983 Feb;5(2):122-39. doi: 10.1109/tpami.1983.4767365.
In recent times a great deal of interest has been shown, amongst the computer vision and robotics research community, in the acquisition of range data for supporting scene analysis leading to remote (noncontact) determination of configurations and space filling extents of three-dimensional object assemblages. This paper surveys a variety of approaches to generalized range finding and presents a perspective on their applicability and shortcomings in the context of computer vision studies.
近年来,计算机视觉和机器人研究领域对获取范围数据以支持场景分析产生了浓厚的兴趣,这有助于实现对三维物体组合的远程(非接触式)配置和空间填充程度的非接触式确定。本文综述了各种广义测距方法,并从计算机视觉研究的角度来看待它们的适用性和缺点。