Scene categorization based on integrated feature description and local weighted feature mapping

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• 作者：Fengcai Li^a  ; [Author Vitae] ; Guanghua Gu^a ; ^b ; ^{guguanghua@ysu.edu.cn}  ; [Author Vitae] ; Chengru Wang^a  ; [Author Vitae]
• 刊名：Computers and Electrical Engineering
• 出版年：2012
• 期刊代码：35_00457906
• 类别：cp
• 出版时间：July, 2012
• 卷：38
• 期：4
• 页码：917-925
• 文件大小：850 K

摘要

Local and global features are considerably important features in computer vision and play an important role in scene categorization task. In this paper, an integrated feature description for scene categorization is constructed. First, we extract a type of extended contextual features for scene images that contain the local gradient information and more comprehensive local structural information. Mapping the local features by using improved LLC (Local-constrained Linear Coding) scheme to form the original image representation; Secondly, a set of global features named 鈥榞ist鈥?are extracted that provide a statistical summary of the spatial layout properties of the scene; Then, the contextual features and 鈥榞ist鈥?features are weighted combined based on their contribution for the integrated feature description, and each image is represented by using LLC scheme. Finally, we perform the scene categorization by libSVM with the HIK (Histogram Intersection Kernel) function. The proposed method achieves a satisfactory average accuracy rate 87.60%on a set of 15-scene categories.