电子学报2012，Vol.40Issue(12)：2472-2480,9.DOI:10.3969/j.issn.0372-2112.2012.12.019
基于随机化视觉词典组和上下文语义信息的目标检索方法
Object Retrieval Method Based on Randomized Visual Dictionaries and Contextual Semantic Information
摘要
Abstract
There arc several problems existing in the conventional bag of visual words methods, such as low tune efficiency and large memory consumption,the synonymy and polysemy of visual words, furthermore,they may fail to return satisfactory results if the object region is inaccurate or if the captured object is too small to be represented with discriminative features. An object retrieval method based on randomized visual dictionaries and contextual semantic information is proposed for the above problems. Firstly, E2LSH (Exact Euclidean Locality Sensitive Hashing) is used, and a group of scalable random visual vocabularies is generated;then,a new object model consisting of contextual semantic information is devised,which is drawn from the visual elements surrounding the query object; finally, the Kullback-Leibler divergence is introduced as a similarity measurement to accomplish object retrieval. Experimental results indicate that the distinguishability of objects is effectively improved and the object retrieval performance method is substantially boosted compared with the traditional methods.关键词
目标检索/上下文语义信息/精确欧氏位置敏感哈希/随机化视觉词典组/K-L散度Key words
object retrieval/ contextual semantic information/ exact Euclidean locality sensitive hashing/randomized visual vocabularies/Kullback-Leibler divergence分类
信息技术与安全科学引用本文复制引用
赵永威,郭志刚,李弼程,高毫林,陈刚..基于随机化视觉词典组和上下文语义信息的目标检索方法[J].电子学报,2012,40(12):2472-2480,9.基金项目
国家自然科学基金(No.60872142) （No.60872142）
全军军事学研究生课题资助项目 （）
