Indoor Scene Recognition Based on the Weighting Spatial Information Fusion
Scene recognition is high level image understanding in machine vision field. It is usually difficult to recognize variety indoor scene of which the characteristics between many classes are changing significantly. This paper proposes an indoor home scene recognition model based on Weighting Spatial Information Fusion of PLSA (WSIF_PLSA), build many PLSA models and SVM classifiers using spatial information of indoor scene and fuse the recognition result with weight. So it is considering not only global visual characteristic but also local visual characteristic. The experiment constructs a database of IHSD which is for indoor home scene recognition and the results shows the higher recognition efficiency with this method.
Indoor Scene Information Fusion Local Semantic Concepts
Zhiliang Wang Rong Wang Xirong Ma
School of Computer & Communication Engineering,University of Science & Technology Beijing,Beijing, 1 School of Automatization,University of Science & Technology Beijing,Beijing, 100083, ChinaSchool of School of Computer & Information Engineering, Tianjin Normal University. Tianjin, 300387,China
国际会议
三亚
英文
1040-1044
2012-01-06（万方平台首次上网日期，不代表论文的发表时间）