Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Context-based friend suggestion in online photo-sharing community
MM '11 Proceedings of the 19th ACM international conference on Multimedia
| Hi-index | 0.00 |
Unlike the questionnaire based friend recommendation scheme used in Social Network Service (SNS) websites nowadays (e.g. online dating sites, online matchmaking sites), we focus on the fact that most of the online users may be interested in the strangers whose appearances are somehow attractive according to their own preferences. In this paper, we present a friend recommendation system based on the appearances on photos. The system is built upon 5000 portraits photos as source dataset with another 50 photos as training set. Once the user provides rating to several photos in the training set, we first build his/her appearance prefe-rence model based on face detection and multi-features cooperation. Then, the images in the source are ranked according to different features respectively. Finally, the results of multi-features are fused via the method of Borda count. The system is a useful complement to the conventional psychological tests based friend rec-ommendation scheme. It is easy to play with and of a lot of fun.