# Large-Scale, Real-World Face Recognition in Movie Trailers Presentation 4 Alan Wright.

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Large-Scale, Real-World Face Recognition in Movie Trailers Presentation 4 Alan Wright

Dictionary Distribution Pub Fig Dictionary (200 people) Number of training images (capped at 200)

Dictionary Distribution Pub Fig Dictionary (200 people) Number of training images (capped at 200)

Preliminary Testing GPSR – Date Night 76.47% accuracy (26/34 tracks) – Accuracy increase from 44% last week. – Looked at confidence rather than only mode. – Adjusted tau parameter to 0.01 – Accurate results, but takes ~320 secs per frame (approx 5 minutes). Face Tracks have anywhere from 8 to 80+ frames.

Preliminary Testing Coefficient Vector Test images in dictionary Frames in Track Tina Fey

Preliminary Testing Coefficient Vector Track is Tina Fey High confidence and high coefficients Exactly what we expected

Preliminary Testing Coefficient Vector Test images in dictionary Frames in Track

Preliminary Testing Coefficient Vector No clear recognition Most likely due to facial expression, lighting, pose, and small number of frames (only 8).

Preliminary Testing Other methods tested: homotopy, DALM, LASRC… Poor accuracy, but faster run times. How can we speed up GPSR?

GPSR Average Approach Y 1 = Ax 1 Y 2 = Ax 2 … Y k = Ax k Simplifies to: Find a single coefficient for an entire track, rather than a coefficient for each frame of the track.

GPSR Average Approach Average each frame of the track (very quick). Pass this average to the face recognition function. It will still take ~320 secs, but won’t take 320 s * x frames.

GPSR Average Results Date Night – 76.47% accuracy (just as accurate as the frame by frame method, but faster). The incorrect matches were on all but 2 of the same face tracks.

GPSR Average Results Preformed just as well on trailer subset (6 trailers) George Bush was IDed in all 3 tracks. Celine Dion was IDed in 4 out of 6 tracks.

GPSR Average Results Jessica Alba was not IDed well Leonardo DiCaprio was not IDed well

What’s Next Finalize Dataset – final face tracks and features. Larger Dataset – Test on more trailers. Look at additional baseline method – low rank approximation (65% accuracy – 60 secs a track) Derive more interesting approximations

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