How to represent scenes for classification?

CORC > 西安光学精密机械研究所 > 中国科学院西安光学精密机械研究所 > 光学影像学习与分析中心

	How to represent scenes for classification?
	Shi, Jianhua1,2 ; Li, Xuelong1 ; Dong, Yongsheng 1
	2015
会议名称	ieee china summit and international conference on signal and information processing, chinasip 2015
会议日期	2015-07
会议地点	chengdu, china
页码	191-195
通讯作者	dong, yongsheng
英文摘要	object-based scene image representations can effectively capture the semantic meanings of a scene. however, they usually neglect a scene's structure information. in this paper, we propose a novel and effective detector-based scene representation method for scene classification. in particular, we extract object features by object detectors. by sensible principal component analysis, we obtain a compact representation vector of objects in a scene image. to capture the scene layout, we then train lots of deformable part models to form a scene response vector. by concatenating these two vectors we use a linear support vector machine for scene classification. when combining with decaf [1] in a special way, our method is even more powerful on complex scene categorization. experimental results on the mit indoor database show that our approach achieves state-of-the-art performance on scene classification compared with several popular methods. © 2015 ieee.
收录类别	EI
产权排序	1
会议录	2015 ieee china summit and international conference on signal and information processing, chinasip 2015 - proceedings
会议录出版者	institute of electrical and electronics engineers inc.
语种	英语
ISBN号	9781479919482
内容类型	会议论文
源URL	[http://ir.opt.ac.cn/handle/181661/27821]
专题	西安光学精密机械研究所_光学影像学习与分析中心
作者单位	1.Center for OPTical IMagery Analysis and Learning (OPTIMAL), State Key Laboratory of Transient Optics and Photonics, Xi'An Institute of Optics and Precision Mechanics, Xi'an, Shaanxi, China 2.University of Chinese Academy of Sciences, 19A Yuquanlu, Beijing, China
推荐引用方式 GB/T 7714	Shi, Jianhua,Li, Xuelong,Dong, Yongsheng. How to represent scenes for classification?[C]. 见:ieee china summit and international conference on signal and information processing, chinasip 2015. chengdu, china. 2015-07.