Binocular Stereo Vision based Indoor Scene Perception
Scene perception aims to build a semantic context for various tasks of visual processing, especially for object recognition. Binocular vision system is now widely equipped with mobile intelligent robots,however, monocular images are currently mostly used for scene perception task. One can obtain lower classification performance by using features extracted from monocular image as the complexity of natural scene. In this paper a binocular stereo vision based approach for scene perception is developed. A feature descriptor of indoor scene is proposed, that is a vector extracted from planes fitting parameters in several specified regions. First step, scene is classified as empty space and close space classes using feature extracted from disparity map with nearest neighbor method. In following step, both empty space and close space scene are classified into some subclasses using Gist and proposed feature descriptor. To test our approach we created a dataset of 4 indoor scenes categories. The experiments show that our approach got excellent classification performance.
binocular stereo vision indoor scene Gist classification
Hong Liu Jiexin Pu Qinghua Zhang
Electronic & Information Engineering College Henan University of Science and Technology Luoyang, Chi Luoyang Sunray Technology Co., Ltd.Luoyang, China
国际会议
上海
英文
34-37
2011-03-11（万方平台首次上网日期，不代表论文的发表时间）