@inproceedings{5d4511c1c69a4430af00cc591427b7d0,
title = "Sparse depth estimation using multi-view 3D modeling",
abstract = "This paper presents a 2D to 3D conversion system from multiple views based on the computation of a sparse depth map. This method is able to deal with the multiple views obtained from uncalibrated hand-held cameras without prior knowledge of the camera parameters or scene geometry. The obtained reconstructed sparse depth maps of feature points in 3D scenes provide accurate relative depth information of the objects. Sample ground-truth depth data points are used to calculate a scale factor in order to estimate the true depth by scaling the obtained relative depth using the estimated scale factor. Results are presented to illustrate the performance of the developed system. It is shown that the implemented 2D to 3D conversion system results in a reconstructed depth map that matches the ground-truth depth data.",
keywords = "3D reconstruction, Depth estimation, Euclidean reconstruction, Multi-view, Sparse depth map",
author = "Jinjin Li and Lina Karam",
year = "2012",
doi = "10.1109/ESPA.2012.6152468",
language = "English (US)",
isbn = "9781467308984",
series = "2012 IEEE International Conference on Emerging Signal Processing Applications, ESPA 2012 - Proceedings",
pages = "151--154",
booktitle = "2012 IEEE International Conference on Emerging Signal Processing Applications, ESPA 2012 - Proceedings",
note = "2012 IEEE International Conference on Emerging Signal Processing Applications, ESPA 2012 ; Conference date: 12-01-2011 Through 14-01-2011",
}