Visual fatigue prediction for stereoscopic image

Donghyun Kim; Kwanghoon Sohn

doi:10.1109/TCSVT.2011.2106275

Visual fatigue prediction for stereoscopic image

Donghyun Kim, Kwanghoon Sohn

Department of Electrical and Electronic Engineering

Research output: Contribution to journal › Article › peer-review

122 Citations (Scopus)

Abstract

In this letter, we propose a visual fatigue prediction metric which can replace subjective evaluation for stereoscopic images. It detects stereoscopic impairments caused by inappropriate shooting parameters or camera misalignment which induces excessive horizontal and vertical disparities. Pearson's correlation was measured between the proposed metrics and the subjective results by using $k$-fold cross-validation, acquiring ranges of 7887% with sparse feature and 7485% with dense feature.

Original language	English
Article number	5688305
Pages (from-to)	231-236
Number of pages	6
Journal	IEEE Transactions on Circuits and Systems for Video Technology
Volume	21
Issue number	2
DOIs	https://doi.org/10.1109/TCSVT.2011.2106275
Publication status	Published - 2011 Feb

Bibliographical note

Funding Information:
Manuscript received December 11, 2009; revised April 2, 2010, May 26, 2010 and September 16, 2010; accepted September 26, 2010. Date of publication January 17, 2011; date of current version March 2, 2011. This work was supported in part by the IT R&D Program of MKE/KCC/KEIT [10035158, quality monitoring and quality assurance for multimedia and 3-D applications] and in part by the MKE, Korea, under the ITRC Support Program supervised by the NIPA (NIPA-2010-C1090-1001-0006). This paper was recommended by Associate Editor S. Yan.

All Science Journal Classification (ASJC) codes

Media Technology
Electrical and Electronic Engineering

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10.1109/TCSVT.2011.2106275

Cite this

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abstract = "In this letter, we propose a visual fatigue prediction metric which can replace subjective evaluation for stereoscopic images. It detects stereoscopic impairments caused by inappropriate shooting parameters or camera misalignment which induces excessive horizontal and vertical disparities. Pearson's correlation was measured between the proposed metrics and the subjective results by using $k$-fold cross-validation, acquiring ranges of 7887% with sparse feature and 7485% with dense feature.",

author = "Donghyun Kim and Kwanghoon Sohn",

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Visual fatigue prediction for stereoscopic image

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

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