Visualizing Image Query Sense by Social Tags

• Main Authors: Wei-Yen Day, 戴瑋彥
• Other Authors: Pu-Jen Cheng
• Format: Others
• Language: en_US
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/51758772231078538634

碩士 === 臺灣大學 === 資訊工程學研究所 === 98 === In this paper, we present an approach for visualizing image query senses. Image queries usually have several senses, which can describe the meanings of themselves. However, senses like ‘hot’ might not be concrete, thus we need to find out visual concepts to visualize these image query senses. We propose a novel approach to discover the visual concepts for image queries based on several statistical scores and social tags from Flickr, and further help improve image search by visualizing their senses. To evaluate the effectiveness of our approach, we test the found concepts on real world queries and images. Both the experimental results, conducted for image retrieval and concepts evaluation, demonstrate that the approach can substantially improve the traditional image search engine, which retrieve only relevant images, and show that the visual concepts for image query senses can be utilized to enhance the effectiveness of image retrieval.