Multi-Scale Image Semantic Recognition with Hierarchical Visual Vocabulary

Computer Science and Information Systems

Tanfeng Sun¹  Xinghao Jiang² 

[1] Key Lab. of Shanghai Information Security Management and Technology Research;School of Information Security Engineering, Shanghai Jiao Tong University

关键词: local feature;    bag of visual words;    image semantic analysis;    visual vocabulary;   

DOI  :  10.2298/CSIS100423035J

学科分类：社会科学、人文和艺术（综合）

来源: Computer Science and Information Systems

【 摘 要 】

Local features have been proved to be effective in image/video semantic analysis. The BOVW (bag of visual words) scheme can cluster local features to form the visual vocabulary which includes an amount of words, where each word is the center of one clustering feature. The vocabulary is used to recognize the image semantic. In this paper, a new scheme to construct semantic-binding hierarchical visual vocabulary is proposed. Some attributes and relationship of the semantic nodes in the model are discussed. The hierarchical semantic model is used to organize the multi-scale semantic into a level-by-level structure. Experiments are performed based on the LabelMe dataset, the performance of our scheme is evaluated and compared with the traditional BOVW scheme, experimental results demonstrate the efficiency and flexibility of our scheme.

【 授权许可】

CC BY-NC-ND