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Computer Graphics Forum
Article . 2015 . Peer-reviewed
License: Wiley Online Library User Agreement
Data sources: Crossref
DBLP
Article . 2015
Data sources: DBLP
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An Image Degradation Model for Depth‐augmented Image Editing

Authors: James W. Hennessey; Niloy J. Mitra;

An Image Degradation Model for Depth‐augmented Image Editing

Abstract

AbstractImages remain the most popular medium to capture our surroundings. Although significant advances have been made in developing image editing tools, the key challenge is to intelligently account for missing depth information. The growing popularity of depth images offers a new avenue to revisit image editing tasks. In this work, we investigate how even coarse depth information can be exploited to address some of the fundamental challenges in image editing namely producing correct perspective, handling occlusion, and obtaining segmentation. To this end, we propose a novel image degradation model that predicts how well an image edit can be performed in presence of coarse depth information. Technically, we create proxy geometry to summarize available depth information, and use it to predict occlusions and ordering between image patches, complete occluded regions, and anticipate image‐level changes under camera movement. We evaluate the proposed image degradation model in the context of parallax photography from single depth images.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Top 10%
bronze