
Proceedings Paper
A computationally efficient approach to 3D point cloud reconstructionFormat | Member Price | Non-Member Price |
---|---|---|
$17.00 | $21.00 |
Paper Abstract
This paper addresses improving the computational efficiency of the 3D point cloud reconstruction pipeline using uncalibrated
image sequences. In existing pipelines, the bundle adjustment is carried out globally, which is quite time
consuming since the computational complexity keeps growing as the number of image frames is increased. Furthermore,
a searching and sorting algorithm needs to be used in order to store feature points and 3D locations. In order to reduce
the computational complexity of the 3D point cloud reconstruction pipeline, a local refinement approach is introduced in
this paper. The results obtained indicate that the introduced local refinement improves the computational efficiency as
compared to the global bundle adjustment.
Paper Details
Date Published: 19 February 2013
PDF: 8 pages
Proc. SPIE 8656, Real-Time Image and Video Processing 2013, 86560O (19 February 2013); doi: 10.1117/12.2000483
Published in SPIE Proceedings Vol. 8656:
Real-Time Image and Video Processing 2013
Nasser Kehtarnavaz; Matthias F. Carlsohn, Editor(s)
PDF: 8 pages
Proc. SPIE 8656, Real-Time Image and Video Processing 2013, 86560O (19 February 2013); doi: 10.1117/12.2000483
Show Author Affiliations
C.-H. Chang, The Univ. of Texas at Dallas (United States)
N. Kehtarnavaz, The Univ. of Texas at Dallas (United States)
N. Kehtarnavaz, The Univ. of Texas at Dallas (United States)
K. Raghuram, Texas Instruments Inc. (United States)
R. Staszewski, Texas Instruments Inc. (United States)
R. Staszewski, Texas Instruments Inc. (United States)
Published in SPIE Proceedings Vol. 8656:
Real-Time Image and Video Processing 2013
Nasser Kehtarnavaz; Matthias F. Carlsohn, Editor(s)
© SPIE. Terms of Use
