Building global image features for scene recognition

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• 作者：Xianglin  ; Meng  ; ;   ; ^{xlmeng@nudt.edu.cn} ; Zhengzhi  ; Wang ; Lizhen  ; Wu[Author vitae]
• 关键词：Scene recognition ; Global image representation ; Local binary pattern ; Census transform
• 刊名：Pattern Recognition
• 出版年：2012
• 出版时间：January 2012
• 年：2012
• 卷：45
• 期：1
• 页码：373-380
• 全文大小：1407 K

文摘

In this paper, we present a simple, yet very efficient global image representation for scene recognition. A scene image is represented by a histogram of local transforms, which is an extended version of census transform histogram. The local transforms include local difference sign and magnitude information. Due to strong constraints between neighboring transformed values, global structure information can be captured through the histogram and spatial pyramid representation. Principal component analysis is used to reduce the dimensionality and get a compact feature vector. Experimental results on three widely used datasets demonstrate that the proposed method could achieve competitive performance in terms of speed and accuracy.