Title
Recovering Specular Surfaces Using Curved Line Images
Abstract
We present a new shape-from-distortion framework for recovering specular (reflective/refractive) surfaces. While most existing approaches rely on accurate correspondences between 2D pixels and 3D points, we focus on analyzing the curved images of 3D lines which we call curved line images or CLIs. Our approach models CLIs of local reflections or refractions using the recently proposed general linear cameras (GLCs)[23]. We first characterize all possible CLIs in a GLC. We show that a 3D line will appear as a conic in any GLC. For a fixed GLC, the conic type is invariant to the position and orientation of the line and is determined by the GLC parameters. Furthermore, CLIs under single reflection/refraction can only be lines or hyperbolas. Based on our new theory, we develop efficient algorithms to use multiple CLIs to recover the GLC camera parameters. We then apply the curvature-GLC theory to derive the Gaussian and mean curvatures from the GLC intrinsics. This leads to a complete distortion-based reconstruction framework. Unlike conventional correspondence-based approaches that are sensitive to image distortions, our approach benefits from the CLI distortions. Finally, we demonstrate applying our framework for recovering curvature fields on both synthetic and real specular surfaces.
Year
DOI
Venue
2009
10.1109/CVPRW.2009.5206624
CVPR: 2009 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOLS 1-4
Keywords
Field
DocType
specular reflection,computational geometry,nonlinear distortion,gaussian curvature,gaussian processes,image reconstruction,computer vision,pixel,robustness,mathematical model,geometry,surface reconstruction,mean curvature
Iterative reconstruction,Computer vision,Curvature,Computer science,Specular reflection,Hyperbola,Artificial intelligence,Conic section,Distortion,Intrinsics,Gaussian curvature
Conference
Volume
Issue
ISSN
2009
1
1063-6919
Citations 
PageRank 
References 
11
0.53
19
Authors
3
Name
Order
Citations
PageRank
Yuanyuan Ding130315.04
Jingyi Yu21238101.25
Peter Sturm32696206.38