Automatic 3D-Display-Friendly Scene Extraction from Video Sequences and Optimal Focusing Distance Identification

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F24%3APU150756" target="_blank" >RIV/00216305:26230/24:PU150756 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/article/10.1007/s11042-024-18573-6" target="_blank" >https://link.springer.com/article/10.1007/s11042-024-18573-6</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s11042-024-18573-6" target="_blank" >10.1007/s11042-024-18573-6</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Automatic 3D-Display-Friendly Scene Extraction from Video Sequences and Optimal Focusing Distance Identification

Popis výsledku v původním jazyce

This paper proposes a method for an automatic detection of 3D-display-friendly scenes from video sequences.  Manual selection of such scenes by a human user would be extremely time consuming and would require additional evaluation of the result on 3D display. The input videos can be intentionally captured or taken from other sources, such as films.  First, the input video is analyzed and the camera trajectory is estimated.  The optimal frame sequence that follows defined rules, based on optical attributes of the display, is then extracted.  This ensures the best visual quality and viewing comfort.  The following identification of a correct focusing distance is an important step to produce a sharp and artifact-free result on a 3D display.  Two novel and equally efficient focus metrics for 3D displays are proposed and evaluated.  Further scene enhancements are proposed to correct the unsuitably captured video. Multiple image analysis approaches used in the proposal are compared in terms of both quality and time performance. The proposal is experimentally evaluated on a state-of-the-art 3D display by Looking Glass Factory and is suitable even for other multi-view devices. The problem of optimal scene detection, which includes the input frames extraction, resampling, and focusing, was not addressed in any previous research. Separate stages of the proposal were compared with existing methods, but the results show that the proposed scheme is optimal and cannot be replaced by other state-of-the-art approaches.

Název v anglickém jazyce

Automatic 3D-Display-Friendly Scene Extraction from Video Sequences and Optimal Focusing Distance Identification

Popis výsledku anglicky

This paper proposes a method for an automatic detection of 3D-display-friendly scenes from video sequences.  Manual selection of such scenes by a human user would be extremely time consuming and would require additional evaluation of the result on 3D display. The input videos can be intentionally captured or taken from other sources, such as films.  First, the input video is analyzed and the camera trajectory is estimated.  The optimal frame sequence that follows defined rules, based on optical attributes of the display, is then extracted.  This ensures the best visual quality and viewing comfort.  The following identification of a correct focusing distance is an important step to produce a sharp and artifact-free result on a 3D display.  Two novel and equally efficient focus metrics for 3D displays are proposed and evaluated.  Further scene enhancements are proposed to correct the unsuitably captured video. Multiple image analysis approaches used in the proposal are compared in terms of both quality and time performance. The proposal is experimentally evaluated on a state-of-the-art 3D display by Looking Glass Factory and is suitable even for other multi-view devices. The problem of optimal scene detection, which includes the input frames extraction, resampling, and focusing, was not addressed in any previous research. Separate stages of the proposal were compared with existing methods, but the results show that the proposed scheme is optimal and cannot be replaced by other state-of-the-art approaches.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

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

Projekt

<a href="/cs/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>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název periodika

MULTIMEDIA TOOLS AND APPLICATIONS

ISSN

1380-7501

e-ISSN

1573-7721

Svazek periodika

83

Číslo periodika v rámci svazku

7

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

29

Strana od-do

1-29

Kód UT WoS článku

001162972300008

EID výsledku v databázi Scopus

2-s2.0-85185139776