1. Large-scale, Real-world facial recognition in movie trailers Alan Wright Presentation 6

2. Cast selector 2

3. Retrieves cast list from Rotten Tomatoes using their API. Ignore tracks we don’t want. Type custom names. Allows two people to simultaneously label tracks and no labeling will be repeated. 3

4. Cast selector All 2400+ tracks have now been labeled with the correct faces. Faces not in PubFig were still labeled. Easily label more tracks if new trailers are added. If faces are added to PubFig, the labeling will not need to be redone. 4

5. Labeling results 635 Unknown tracks 712 PubFig tracks 1113 labeled tracks (faces not in PubFig) 4 ignored tracks.

6. Labeling results PubFig Ids # of labels

7. Labeling results Katherine Heigl was labeled the most with 51 tracks. Each PubFig face (in the trailers) has an average of 12 tracks.

8. Labeling Results The most labeled face not in PubFig was Edward Norton with 53 tracks. 218 faces were labeled, but not in PubFig. Average of 5 tracks per face.

9. What’s next Generate new PR curves with labels (Expected Thursday) Reassess algorithm performance