Steven M. Seitz and Simon Baker
The filter flow problem is to compute a space-variant linear filter that transforms one image into another. This framework encompasses a broad range of transformations including stereo, optical flow, lighting changes, blur, and combinations of these effects. Parametric models such as affine motion, vignetting, and radial distortion can also be modeled within the same framework. All such transformations are modeled by selecting a number of constraints and objectives on the filter entries from a catalog which we enumerate. Most of the constraints are linear, leading to globally optimal solutions (via linear programming) for affine transformations, depth-from-defocus, and other problems. Adding a (non-convex) compactness objective enables solutions for optical flow with illumination changes, spacevariant defocus, and higher-order smoothness.
In Proceedings of the IEEE International Conference on Computer Vision
Publisher IEEE Computer Society
Copyright © 2007 IEEE. Reprinted from IEEE Computer Society. This material is posted here with permission of the IEEE. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to email@example.com. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.