Title :
A Theory of Refractive Photo-Light-Path Triangulation
Author :
Chari, Visesh ; Sturm, Peter
Author_Institution :
Projet WILLOW, INRIA Paris, Paris, France
Abstract :
3D reconstruction of transparent refractive objects like a plastic bottle is challenging: they lack appearance related visual cues and merely reflect and refract light from the surrounding environment. Amongst several approaches to reconstruct such objects, the seminal work of Light-Path triangulation is highly popular because of its general applicability and analysis of minimal scenarios. A light-path is defined as the piece-wise linear path taken by a ray of light as it passes from source, through the object and into the camera. Transparent refractive objects not only affect the geometric configuration of light-paths but also their radiometric properties. In this paper, we describe a method that combines both geometric and radiometric information to do reconstruction. We show two major consequences of the addition of radiometric cues to the light-path setup. Firstly, we extend the case of scenarios in which reconstruction is plausible while reducing the minimal requirements for a unique reconstruction. This happens as a consequence of the fact that radiometric cues add an additional known variable to the already existing system of equations. Secondly, we present a simple algorithm for reconstruction, owing to the nature of the radiometric cue. We present several synthetic experiments to validate our theories, and show high quality reconstructions in challenging scenarios.
Keywords :
computational geometry; image reconstruction; light reflection; light refraction; 3D transparent refractive object reconstruction; appearance related visual cues; geometric configuration; light reflection; light refraction; plastic bottle; radiometric properties; refractive photo-light-path triangulation theory; system-of-equations; Cameras; Equations; Image reconstruction; Monitoring; Radiometry; Refractive index; Surface reconstruction; Light path triangulation; Minimal Solution; Photometry; Radiometry; Reconstruction;
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on
Conference_Location :
Portland, OR
DOI :
10.1109/CVPR.2013.189