Lightweight All-Focused Light Field Rendering

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F24%3APU151479" target="_blank" >RIV/00216305:26230/24:PU151479 - isvavai.cz</a>

Result on the web

<a href="https://www.sciencedirect.com/science/article/abs/pii/S1077314224001127" target="_blank" >https://www.sciencedirect.com/science/article/abs/pii/S1077314224001127</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.cviu.2024.104031" target="_blank" >10.1016/j.cviu.2024.104031</a>

Result language

angličtina

Original language name

Lightweight All-Focused Light Field Rendering

Original language description

This paper proposes a novel real-time method for high-quality view interpolation from light field. The proposal is a lightweight method, which can be used with consumer GPU, reaching same or better quality than existing methods, in a shorter time, with significantly smaller memory requirements. Light field belongs to image-based rendering methods that can produce realistic images without computationally demanding algorithms. The novel view is synthesized from multiple input images of the same scene, captured at different camera positions. Standard rendering techniques, such as rasterization or ray-tracing, are limited in terms of quality, memory footprint, and speed. Light field rendering methods often produce unwanted artifacts resembling ghosting or blur in certain parts of the scene due to unknown geometry of the scene. The proposed method estimates the geometry for each pixel as an optimal focusing distance to mitigate the artifacts. The focusing distance determines which pixels from the input images are mixed to produce the final view. State-of-the-art methods use a constant-step pixel matching scan that iterates over a range of focusing distances. The scan searches for a distance with the smallest color dispersion of the contributing pixels, assuming that they belong to the same spot in the scene. The paper proposes an optimal scanning strategy of the focusing range, an improved color dispersion metric, and other minor improvements, such as sampling block size adjustment, out-of-bounds sampling, and filtering. Experimental results show that the proposal uses less resources, achieves better visual quality, and is significantly faster than existing light field rendering methods. The proposal is 8× faster than the methods in the same category. The proposal uses only four closest views from the light field data and reduces the necessary data transfer. Existing methods often require the full light field grid, which is typically 8×8 images l

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/8A21015" target="_blank" >8A21015: AI-augmented automation for efficient DevOps, a model-based framework for continuous development At RunTime in cyber-physical systems</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

COMPUTER VISION AND IMAGE UNDERSTANDING

ISSN

1077-3142

e-ISSN

1090-235X

Volume of the periodical

244

Issue of the periodical within the volume

7

Country of publishing house

US - UNITED STATES

Number of pages

16

Pages from-to

7-8

UT code for WoS article

001238000300001

EID of the result in the Scopus database

2-s2.0-85192206398