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 | |
| Publication status | Published - 2011 Feb 1 |
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All Science Journal Classification (ASJC) codes
- Media Technology
- Electrical and Electronic Engineering
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Visual fatigue prediction for stereoscopic image. / Kim, Donghyun; Sohn, Kwanghoon.
In: IEEE Transactions on Circuits and Systems for Video Technology, Vol. 21, No. 2, 5688305, 01.02.2011, p. 231-236.Research output: Contribution to journal › Article
TY - JOUR
T1 - Visual fatigue prediction for stereoscopic image
AU - Kim, Donghyun
AU - Sohn, Kwanghoon
PY - 2011/2/1
Y1 - 2011/2/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=79952021066&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79952021066&partnerID=8YFLogxK
U2 - 10.1109/TCSVT.2011.2106275
DO - 10.1109/TCSVT.2011.2106275
M3 - Article
AN - SCOPUS:79952021066
VL - 21
SP - 231
EP - 236
JO - IEEE Transactions on Circuits and Systems for Video Technology
JF - IEEE Transactions on Circuits and Systems for Video Technology
SN - 1051-8215
IS - 2
M1 - 5688305
ER -