Benchmarking of several disparity estimation algorithms for light field processing
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
Details
| Original language | English |
|---|---|
| Title of host publication | Fourteenth International Conference on Quality Control by Artificial Vision |
| Editors | Stephane Bazeille, Nicolas Verrier, Christophe Cudel |
| Publisher | SPIE, IEEE |
| ISBN (Electronic) | 9781510630536 |
| DOIs | |
| Publication status | Published - 2019 |
| Publication type | A4 Article in a conference publication |
| Event | International Conference on Quality Control by Artificial Vision - Mulhouse, France Duration: 15 May 2019 → 17 May 2019 |
Publication series
| Name | Proceedings of SPIE - The International Society for Optical Engineering |
|---|---|
| Volume | 11172 |
| ISSN (Print) | 0277-786X |
| ISSN (Electronic) | 1996-756X |
Conference
| Conference | International Conference on Quality Control by Artificial Vision |
|---|---|
| Country | France |
| City | Mulhouse |
| Period | 15/05/19 → 17/05/19 |
Abstract
A number of high-quality depth imaged-based rendering (DIBR) pipelines have been developed to reconstruct a 3D scene from several images taken from known camera viewpoints. Due to the specific limitations of each technique, their output is prone to artifacts. Therefore, the quality cannot be ensured. To improve the quality of the most critical and challenging image areas, an exhaustive comparison is required. In this paper, we consider three questions of benchmarking the quality performance of eight DIBR techniques on light fields: First, how does the density of original input views affect the quality of the rendered novel views? Second, how does disparity range between adjacent input views impact the quality? Third, how does each technique behave for different object properties? We compared and evaluated the results visually as well as quantitatively (PSNR, SSIM, AD, and VDP2). The results show some techniques outperform others in different disparity ranges. The results also indicate using more views not necessarily results in visually higher quality for all critical image areas. Finally, we have shown a comparison for different scene's complexity such as non-Lambertian objects.
ASJC Scopus subject areas
Keywords
- Depth image-based rendering, Disparity estimation, Quality evaluation