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
Link To Document :
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