关键词: 贝叶斯, 吉布斯分布, 高斯分布, 短线段

Abstract: This paper presents a new approach to recognize the object of building in complex scenes. It extracts a set of line segments ,and turns object recognition into maximum a posteriori estimation. The prior knowledge can be incorporated into target identification process by using Bayesian theory. A new distribution is proposed to model the uncertainty of model features based on Gibbs distribution , which captures phenomena such as the fact that unmatched features due to partial occlusion are generally spatially correlated rather than independent. Fluctuations of matched image features are modeled by Gauss distribution. Finally, a score is proposed to evaluate the region of image，where buildings may exist . Experiments on the natural image sets demonstrated that the proposed score to a certain extent can differentiate between the true object and the false object in complex scenes, and the proposed approach yields substantial improvements over the traditional approach based on edge feature on time performance.

Key words: Bayesian, Gibbs distribution, Gauss distribution, Short line segment