Name
Title | ||
|---|---|---|
Computationally efficient approach to three-dimensional point cloud reconstruction from video image sequences |
Abstract | ||
|---|---|---|
This paper presents a computationally efficient solution to three-dimensional point cloud reconstruction from video image sequences that are captured by a hand-held camera. Our solution starts with a frame selection step to remove frames that cause physically nonrealizable reconstruction outcomes. Then, a computationally efficient approach for obtaining the absolute camera pose is introduced based on pair-wise relative camera poses. This is followed by a computationally efficient rotation registration to update the absolute camera pose. The reconstruction results obtained based on actual video sequences indicate lower computation times and lower reprojection errors of the introduced approach compared to the conventional approach. (C) 2014 SPIE and IS&T |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1117/1.JEI.23.3.033020 | JOURNAL OF ELECTRONIC IMAGING |
Keywords | Field | DocType |
computationally efficient 3-D point cloud reconstruction,frame selection for 3-D reconstruction,computationally efficient relative camera pose estimation and rotation registration | Pairwise comparison,Computer vision,Computer science,Matrix (mathematics),Artificial intelligence,Point cloud,Computation | Journal |
Volume | Issue | ISSN |
23 | 3 | 1017-9909 |
Citations | PageRank | References |
1 | 0.36 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chih-Hsiang Chang | 1 | 103 | 10.91 |
| Nasser D. Kehtarnavaz | 2 | 534 | 66.02 |