期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2015
卷号：6
期号：4
页码：3825-3829
出版社：TechScience Publications
摘要：Due to the popularity of image capturing digital devices and the ease of social network/photo sharing services (e.g., Facebook, Twitter, Flickr), there are largely growing consumer photos available in database. Thus, with the exponentially growing photos, large-scale content-based face image retrieval is an enabling technology for many emerging applications. In this face image retrieval system, aim is to utilize automatically detected human attributes that contain semantic cues of the face photos to improve face retrieval by constructing semantic codewords for efficient large-scale face image retrieval. In this work, low level features and high level attributes are used to represent facial images and regression technique is applied to improve retrieval result. Experimental result shows that, proposed face image retrieval framework achieved more accuracy as compared to the existing methods.
关键词：content-based image retrieval; human attribute;detection; sparse coding; content-based face image retrieval;sparse codewords.
