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Proceedings Paper

A computationally efficient pipeline for 3D point cloud reconstruction from video sequences
Author(s): Chih-Hsiang Chang; Nasser Kehtarnavaz
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Paper Abstract

This paper presents a computationally efficient pipeline to achieve 3D point cloud reconstruction from video sequences. This pipeline involves a key frame selection step to improve the computational efficiency by generating reliable depth information from pair-wise frames. An outlier removal step is then applied in order to further improve the computational efficiency. The reconstruction is achieved based on a new absolute camera pose recovery approach in a computationally efficient manner. This pipeline is devised for both sparse and dense 3D reconstruction. The results obtained from video sequences exhibit higher computational efficiency and lower re-projection errors of the introduced pipeline compared to the existing pipelines.

Paper Details

Date Published: 14 May 2018
PDF: 12 pages
Proc. SPIE 10670, Real-Time Image and Video Processing 2018, 106700B (14 May 2018); doi: 10.1117/12.2302674
Show Author Affiliations
Chih-Hsiang Chang, The Univ. of Texas at Dallas (United States)
Nasser Kehtarnavaz, The Univ. of Texas at Dallas (United States)


Published in SPIE Proceedings Vol. 10670:
Real-Time Image and Video Processing 2018
Nasser Kehtarnavaz; Matthias F. Carlsohn, Editor(s)

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