Super Resolution Optical Flow

Simon Baker and Takeo Kanade
tech. report CMU-RI-TR-99-36, Robotics Institute, Carnegie Mellon University, October, 1999


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Abstract
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 present 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. In this paper we describe an initial implementation of super-resolution optical flow, present detailed experimental results, and describe the relationship between super-resolution optical flow and pyramid-based image representations such as the Laplacian pyramid.

Keywords
Super Resolution, Optical Flow, Video Enhancement, Face Recognition

Notes
Associated Center(s) / Consortia: Vision and Autonomous Systems Center
Associated Lab(s) / Group(s): Face Group
Associated Project(s): Image Enhancement for Faces and Super-Resolution Optical Flow

Text Reference
Simon Baker and Takeo Kanade, "Super Resolution Optical Flow," tech. report CMU-RI-TR-99-36, Robotics Institute, Carnegie Mellon University, October, 1999

BibTeX Reference
@techreport{Baker_1999_3190,
   author = "Simon Baker and Takeo Kanade",
   title = "Super Resolution Optical Flow",
   booktitle = "",
   institution = "Robotics Institute",
   month = "October",
   year = "1999",
   number= "CMU-RI-TR-99-36",
   address= "Pittsburgh, PA",
}