Paper Info
Title
Improving Computational Efficiency of 3D Point Cloud Reconstruction from Image Sequences
Abstract
The Levenberg-Marquardt optimization is normally used in 3D point cloud reconstruction from image sequences which is computationally expensive. This paper presents a two-stage camera pose estimation approach where an initial camera pose is obtained during the first stage and a refinement is performed during the second stage. This approach does not require the use of the Levenberg-Marquardt optimization and LU matrix decomposition for computing the projection matrix, thus providing a more computationally efficient 3D point cloud reconstruction as compared to the existing approaches. The results obtained using real video sequences indicate that the introduced approach generates lower re-projection errors as well as faster 3D point cloud reconstruction.
Year
DOI
Venue
2013
10.1109/ISM.2013.101
ISM
Keywords
DocType
Citations 
image sequence,point cloud reconstruction,initial camera,lower re-projection error,lu matrix decomposition,image sequences,levenberg-marquardt optimization,projection matrix,two-stage camera,improving computational efficiency,existing approach,estimation approach,pose estimation,computer graphics,matrix decomposition,image reconstruction
Conference
0
PageRank 
References 
Authors
0.34
7
2
Name
Order
Citations
PageRank
Chih-Hsiang Chang110310.91
Nasser D. Kehtarnavaz253466.02