Denoising of 3D point clouds constructed from light fields

Christian Galea 1 Christine Guillemot 1
1 Sirocco - Analysis representation, compression and communication of visual data
Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : Light fields are 4D signals capturing rich information from a scene. The availability of multiple views enables scene depth estimation, that can be used to generate 3D point clouds. The constructed 3D point clouds, however, generally contain distortions and artefacts primarily caused by inaccuracies in the depth maps. This paper describes a method for noise removal in 3D point clouds constructed from light fields. While existing methods discard outliers, the proposed approach instead attempts to correct the positions of points, and thus reduce noise without removing any points, by exploiting the consistency among views in a light-field. The proposed 3D point cloud construction and denoising method exploits uncertainty measures on depth values. We also investigate the possible use of the corrected point cloud to improve the quality of the depth maps estimated from the light field.
Document type :
Conference papers
Complete list of metadatas

Cited literature [16 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-02116377
Contributor : Christine Guillemot <>
Submitted on : Tuesday, April 30, 2019 - 9:38:42 PM
Last modification on : Monday, December 9, 2019 - 2:45:24 PM

File

icassp2019_3DPC.pdf
Files produced by the author(s)

Identifiers

Citation

Christian Galea, Christine Guillemot. Denoising of 3D point clouds constructed from light fields. ICASSP 2019 - IEEE International Conference on Acoustics, Speech, and Signal Processing, May 2019, Brighton, United Kingdom. pp.1882-1886, ⟨10.1109/ICASSP.2019.8683548⟩. ⟨hal-02116377⟩

Share

Metrics

Record views

59

Files downloads

110