Improved Bags-of-Words Algorithm for Scene Recognition

摘要：

This paper proposes an effective method to scene recognition based on bags-of-words (BoW) algorithm. Current scene classification methods usually treat all the codewords equally important when using BoW histogram to represent an image. This assumption, however, does not comply with many real-world conditions as different codewords usually have different discriminating power when representing different scene categories. Considering this, this paper proposes an effective technique to perform scene recognition. It first uses k means algorithm to construct a codebook in addition with an occurrence matrix. The im portance of each codeword for each scene category is then estimated based on the above co occurrence matrix. Finally this discrimination information is incorporated into the original BoW histogram of the image and produces a new BoW histogram Support vector machine (SVM) is used to train these BoW histograms. Experimental results on the 15 scene dataset show that the proposed method is very effective compared with state-of-art works.

关键词： scene recognition bags-of-words (BoW) codebook co-occurrence matrix

作者: Jiang Hao Xu Jie

作者单位: School of Information and Electrical Engineering Zhejiang University City College,Hangzhou,China

会议类型: 国际会议

会议名称: 2010 2nd International Conference on Signal Processing System(2010年信号处理系统国际会议 ICSPS 2010)

会议地点: 大连

会议语种:英文

页码: 1119-1122

在线出版日期: 2010-07-05（万方平台首次上网日期，不代表论文的发表时间）