DocumentCode
3326117
Title
Sparse depth estimation using multi-view 3D modeling
Author
Li, Jinjin ; Karam, Lina J.
Author_Institution
Sch. of Electr., Comput. & Energy Eng., Arizona State Univ., Tempe, AZ, USA
fYear
2012
fDate
12-14 Jan. 2012
Firstpage
151
Lastpage
154
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
cameras; image reconstruction; 2D conversion system; 3D conversion system; 3D reconstruction; ground-truth depth data points; multiview 3D modeling; sparse depth estimation; uncalibrated hand-held cameras; Cameras; Estimation; Feature extraction; Geometry; Image reconstruction; Measurement; Three dimensional displays; 3D reconstruction; Depth estimation; Euclidean reconstruction; Multi-view; Sparse depth map;
fLanguage
English
Publisher
ieee
Conference_Titel
Emerging Signal Processing Applications (ESPA), 2012 IEEE International Conference on
Conference_Location
Las Vegas, NV
Print_ISBN
978-1-4673-0899-1
Type
conf
DOI
10.1109/ESPA.2012.6152468
Filename
6152468
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