Codebook Reconstruction with Word Correlation Feedback Mechanism

CASIA OpenIR > 智能感知与计算研究中心

	Codebook Reconstruction with Word Correlation Feedback Mechanism
	Yuhang Zhao; Zhaoxiang Zhang; Yunhong Wang
	2011-08-12
会议名称	International Conference on Image and Graphics
会议录名称	ICIG 2011
会议日期	12-15 August 2011
会议地点	Hefei, China
摘要	Bag of feature model has been shown to be one of the most successful methods in generic image categorization problems. However, creating codebook by clustering local feature vectors (e.g. Kmeans) may lose holistic information of images. This paper presents a novel process called Correlation Feedback for codebook construction. It introduces semantic similarities of words by measuring correlation between distributions of them within one image. Further more, we employ label propagation process to spread the affinities among all features. An enhanced codebook is constructed based on fusion of the new similarity matrix with spectral clustering. Experimental results on Caltech101 and the 15 nature scenes datasets shows promising performance of importing the novel similarity to dictionary construction.
关键词	Spectral Clustering Codebook Reconstruction
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/13295
专题	智能感知与计算研究中心
通讯作者	Zhaoxiang Zhang
推荐引用方式 GB/T 7714	Yuhang Zhao,Zhaoxiang Zhang,Yunhong Wang. Codebook Reconstruction with Word Correlation Feedback Mechanism[C],2011.