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：2000
卷号：XXXIII Part B2
页码：33-40
出版社：Copernicus Publications
摘要：Information technology is increasingly used to support civil infrastructure systems that are large, complexheterogeneous, and distributed. These dynamic systems include communication systems, roads, bridges, traffic controlfacilities, and facilities for the distribution of water, gas and electricity. Mobile mapping is a new technology to capturegeoreferenced data. It is, however, still not practical to extract spatial and attribute information of infrastructure objectsfully automatically.In this article, a framework for 3D-object recognition is proposed according to a viewpoint dependent theory. A novelsystem that generates hot-spot maps using color indexing and edge gradient indexing and recognizes traffic lights usingMCMC (Markov Chain Monte Carlo) method is proposed. The hot-spot map generation method we developed is muchfaster than general color image segmentation and thus is practical to be applied in a recognition system. In thisapproach, both top-down and bottom-up methods are combined by the MCMC engine, which not only recognizestraffic lights but also tells us their poses. This system is robust for different degrees of illumination and rotation
关键词：Markov Chain Monte Carlo; Gibbs distribution; Object Recognition; Color Image
