Name
Abstract | ||
|---|---|---|
This paper examines large partial occlusions in an image which occur near depth discontinuities when the foreground object is severely out of focus. We model these partial occlusions using matting, with the alpha value determined by the convolution of the blur kernel with a pinhole projection of the occluder. The main contribution is a method for removing the image contribution of the foreground occluder in regions of partial occlusion, which improves the visibility of the background scene. The method consists of three steps. First, the region of complete occlusion is estimated using a curve evolution method. Second, the alpha value at each pixel in the partly occluded region is estimated. Third, the intensity contribution of the foreground occluder is removed in regions of partial occlusion. Experiments demonstrate the method's ability to remove the effects of partial occlusion in single images with minimal user input. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/TPAMI.2010.187 | Pattern Analysis and Machine Intelligence, IEEE Transactions |
Keywords | Field | DocType |
curve fitting,hidden feature removal,image restoration,alpha value,blur kernel convolution,curve evolution method,partial occlusion,photographic images,pinhole projection,Focus,curve evolution.,matting,partial occlusion | Aperture,Kernel (linear algebra),Computer vision,Visibility,Occlusion,Pattern recognition,Curve fitting,Convolution,Computer science,Artificial intelligence,Pixel,Image restoration | Journal |
Volume | Issue | ISSN |
33 | 3 | 0162-8828 |
Citations | PageRank | References |
7 | 0.50 | 17 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Scott McCloskey | 1 | 18 | 2.61 |
| michael langer | 2 | 24 | 5.77 |
| Kaleem Siddiqi | 3 | 3259 | 242.07 |