1. Face Clustering in Movies Using Automatically Constructed Social Networks 指導教授 : 葉梅珍 教授 研究生 : 吳文博

2. Outline  Introduction  Approach Preprocessing Appearance-prediction Model Roles’ Social Network Construction Improving Face Clustering Using Social Network  Experimental Results  Conclusions

3. Outline  Introduction  Approach Preprocessing Appearance-prediction Model Roles’ Social Network Construction Improving Face Clustering Using Social Network  Experimental Results  Conclusions

4. Introduction System workflow Movie Appearance- prediction model Face clustering Roles’ social network construction Co-appearance information and shot alternation cues Roles’ social network analysis and feedback to face clustering Preprocessing

5. Outline  Introduction  Approach Preprocessing Appearance-prediction Model Roles’ Social Network Construction Improving Face Clustering Using Social Network  Experimental Results  Conclusions

6. Approach Appearance-prediction Model Memory: generic identity data set(192*5*5) 129 identities from the Multi-PIE data set 5 different pose: -40% to +40% to cover the horizontal in-plane rotation 5 different illumination: no-flash, left-flash, left-right-flash, right-flash, little-flash

7. Approach Appearance-prediction Model The framework of the appearance-prediction model

8. Approach Appearance-prediction Model