Parameterized Variety for Multi-view Multi-exposure Image Synthesis & High Dynamic Range Stereo Reconstruction
Mansi Sharma, Santanu Chaudhury, and Brejesh Lall
3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON), 2012
Abstract
Multi-view stereo, novel view synthesis and high dynamic range (HDR) imaging are three pertinent areas of concern for high quality 3D view generation. This paper presents a novel parameterized variety based model that integrates these different domains into one common framework with an envisioned goal, to accommodate multi-view stereo for multiple exposure input views and to render photo-realistic HDR images from arbitrary virtual viewpoints for high quality 3D reconstruction. We extend the parameterized variety approach for rendering presented earlier by Genc and Ponce [1] to handle full perspective cameras. An efficient algebraic framework is proposed to construct an explicit parameterization of the space of all multi-view multi-exposed images. This characterization of differently exposed views allow to simultaneously recover artifacts free HDR images, and reliable depth maps from arbitrary camera viewpoints. High quality, HDR textured 3D model of the scene is obtained using these images and recovered geometry information.
3DTVCON2012CRpaper.pdfCitation
Mansi Sharma, Santanu Chaudhury, Brejesh Lall. Parameterized variety for multi-view multi-exposure image synthesis and high dynamic range stereo reconstruction. 2012 3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON), Zurich, 2012, pp. 1-4. doi: 10.1109/3DTV.2012.6365450
BibTeX
@INPROCEEDINGS{6365450,
author={M. Sharma and S. Chaudhury and B. Lall},
booktitle={2012 3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON)},
title={Parameterized variety for multi-view multi-exposure image synthesis and high dynamic range stereo reconstruction},
year={2012},
pages={1-4},
doi={10.1109/3DTV.2012.6365450},
ISSN={2161-2021},
month={Oct}
}