Super-Resolution Optical Flow - Robotics Institute Carnegie Mellon University
Super-Resolution Optical Flow

Existing approaches to super-resolution are not applicable to videos of faces because faces are non-planar, non-rigid, non-lambertian, and are subject to self occlusion. We propose super-resolution optical flow as a solution to these problems. Super-resolution optical flow takes as input a conventional video stream, and simultaneously computes both optical flow and a super-resolution version of the entire video. An example of the algorithm is included below. The input consists of a short video, 5 frames of which are:


The output of our algorithm on those 5 frames is:


A complete video output is:

 
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  • Simon Baker

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  • Simon Baker