Photo Tagging Recommendation Using Group Prior on Social Network

• Main Authors: Chean, Yee-Choy, 曾億才
• Other Authors: Lee, Suh-Yin
• Format: Others
• Language: en_US
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/85021606625886861550

碩士 === 國立交通大學 === 資訊科學與工程研究所 === 100 === In social networking sites, photo images that are captured in the daily life occupy a large proportion of web contents since most of people like to upload their photos to share their activities. For sharing a photo with the people appearing in this photo, the users have to manually tag the people with their names, and then the system will recommend this photo to the people immediately. Thus, face tagging becomes a mechanism for photo sharing on the social networking sites, which makes face recognition on the social networking sites become a modern and useful application. Therefore, more and more researches discuss the use of face recognition on the social networking sites to help people tag the photo automatically. However, traditional approaches which use face recognition to recognize people in the social network are not a robust technique for the large number of people and the uncontrolled situation in photos. Hence, the social contexts, which are kinds of user relationship learned from the online social network, are adopted to improve the accuracy of face recognition. In this thesis, we propose a novel system to address the task of tagging recommendation for a photo. Not only the face recognition technique but also the relationship among the people on social network is considered. Different from other studies that just use the relationship between the uploading user and the faces which will be tagged, we also utilize the group relationship of the faces appear in the photo. The experiments show that the recognition performance is truly improved employing the proposed mechanism.