Paper Info
Title
High-quality Depth Estimation Using an Exemplar 3D Model for Stereo Conversion
Abstract
High-quality depth painting for each object in a scene is a challenging task in 2D to 3D stereo conversion. One way to accurately estimate the varying depth within the object in an image is to utilize existing 3D models. Automatic pose estimation approaches based on 2D-3D feature correspondences have been proposed to obtain depth from a given 3D model. However, when the 3D model is not identical to the target object, previous methods often produce erroneous depth in the vicinity of the silhouette of the object. This paper introduces a novel 3D model-based depth estimation method that effectively produces high-quality depth information for rigid objects in a stereo conversion workflow. Given an exemplar 3D model and user correspondences, our method generates detailed depth of an object by optimizing the initial depth obtained by the application of structural fitting and silhouette matching in the image domain. The final depth is accurate up to the given 3D model, while consistent with the image. Our method was applied to various image sequences containing objects with different appearances and varying poses. The experiments show that our method can generate plausible depth information that can be utilized for high-quality 2D to 3D stereo conversion.
Year
DOI
Venue
2015
10.1109/TVCG.2015.2398440
IEEE Transactions on Visualization and Computer Graphics
Keywords
Field
DocType
Depth estimation, 2D-to-3D conversion, stereoscopic 3D, model deformation, pose estimation
Computer vision,Pattern recognition,Silhouette,Computer science,Stereoscopy,2D to 3D conversion,3D pose estimation,Pose,Solid modeling,Artificial intelligence,Workflow
Journal
Volume
Issue
ISSN
PP
99
1077-2626
Citations 
PageRank 
References 
5
0.47
28
Authors
5
Name
Order
Citations
PageRank
Jungjin Lee150.81
Younghui Kim2587.55
Sangwoo Lee35315.00
Bumki Kim4262.38
Jun-yong Noh5113.58