著者
小西 克巳 遠山 敏章 渡辺 明日香
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.25, no.1, pp.25-36, 2010 (Released:2010-01-06)
参考文献数
20

This paper proposes a fashion-related image gathering algorithm and a retrieval system. Since it is difficult to define the fashion-related image exactly in mathematical sense, computers can not recognize whether given images are fashion-related even if they use computer vision techniques. It is also difficult to gather and search only fashion-related images on the Internet automatically for the same reason. In order to overcome these difficulties, we focus on human computing power, which helps computers to find fashion-related images from tons of images on the Internet. This paper provides an algorithm to gather high quality fashion-related images and propses a fashion-related image retrieval system, both of which utilize the information and meta data obtained in a fashion-related image sharing site. Evaluation experiments show that the proposed algorithm can gather fashion-related images efficiently and that the proposed retrival system can find desired images more effectively than Google Image Search.
著者
小西 克巳 遠山 敏章 渡辺 明日香
出版者
The Japanese Society for Artificial Intelligence
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.25, no.1, pp.25-36, 2010

This paper proposes a fashion-related image gathering algorithm and a retrieval system. Since it is difficult to define the fashion-related image exactly in mathematical sense, computers can not recognize whether given images are fashion-related even if they use computer vision techniques. It is also difficult to gather and search only fashion-related images on the Internet automatically for the same reason. In order to overcome these difficulties, we focus on human computing power, which helps computers to find fashion-related images from tons of images on the Internet. This paper provides an algorithm to gather high quality fashion-related images and propses a fashion-related image retrieval system, both of which utilize the information and meta data obtained in a fashion-related image sharing site. Evaluation experiments show that the proposed algorithm can gather fashion-related images efficiently and that the proposed retrival system can find desired images more effectively than Google Image Search.