Prediction of visual discomfort of stereoscopic images based on saliency analysis

SHAO Feng; JIANG Qiu-ping; JIANG Gang-yi; YU Mei

doi:10.3788/OPE.20142206.1631

您当前的位置：

首页 >

文章列表页 >

Prediction of visual discomfort of stereoscopic images based on saliency analysis

更新时间：2020-08-13

- Prediction of visual discomfort of stereoscopic images based on saliency analysis
- Optics and Precision Engineering Vol. 22, Issue 6, Pages: 1631-1638(2014)
- 作者机构：
  
  宁波大学信息科学与工程学院,浙江宁波,315211
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20142206.1631
  CLC： TP391.4
- Received：16 October 2013，
  
  Revised：06 December 2013，
  
  Published：25 June 2014
- 稿件说明：
移动端阅览
邵枫, 姜求平, 蒋刚毅等. 基于显著性分析的立体图像视觉舒适度预测[J]. 光学精密工程, 2014,22(6): 1631-1638

SHAO Feng, JIANG Qiu-ping, JIANG Gang-yi etc. Prediction of visual discomfort of stereoscopic images based on saliency analysis[J]. Editorial Office of Optics and Precision Engineering, 2014,22(6): 1631-1638
邵枫, 姜求平, 蒋刚毅等. 基于显著性分析的立体图像视觉舒适度预测[J]. 光学精密工程, 2014,22(6): 1631-1638 DOI： 10.3788/OPE.20142206.1631.

SHAO Feng, JIANG Qiu-ping, JIANG Gang-yi etc. Prediction of visual discomfort of stereoscopic images based on saliency analysis[J]. Editorial Office of Optics and Precision Engineering, 2014,22(6): 1631-1638 DOI： 10.3788/OPE.20142206.1631.

摘要

分析了传统的基于全局视差特性的像视觉舒适度评价模型的不足，提出了一种基于显著性分析的立体图像视觉舒适度客观预测模型。首先，根据人眼的立体视觉注意力机制，利用协方差矩阵和Sigma特征集分别计算得到图像显著图和深度显著图，并组合得到立体显著图；然后，利用立体显著图加权得到立体图像视觉舒适度感知特征；最后，通过支持向量回归构造视觉舒适度预测函数，建立视觉舒适度感知特征和主观评价值之间的关系模型，从而预测得到立体图像视觉舒适度客观评价值。实验结果表明，本文评价方法的Pearson线性相关系数值达到0.79，Spearman等级相关系数值达到0.81，表明提出的模型更加符合人眼视觉特性，得到的客观评价值与主观感知具有较高的一致性。

Abstract

The drawbacks of the traditional visual comfort assessment metrics for stereoscopic images by using only global disparity features were analyzed. An objective visual discomfort prediction model of stereoscopic images was proposed based on visual saliency analysis. Firstly

an image saliency map and a depth saliency map were calculated by using covariance matrices and Sigma feature sets respectively according to the stereo visual attention mechanism of human eyes and the stereoscopic saliency map was obtained by combination of the two calculations. Then

visual discomfort perceptual features were obtained by using the stereoscopic saliency map as weighting. Finally

the relationship between the visual discomfort perceptual features and the subjective scores was established by constructing a visual discomfort prediction function with support-vector regression

and the objective visual comfort scores were predicted. Experimental results show that the Pearson Linear Correlation Coefficient (PLCC) index of the proposed method reaches 0.79

and the Spearman Rank Order Correlation Coefficient (SRCC) index reaches 0.81. These results indicate that the proposed model can achieve higher consistency with subjective perceptual of stereoscopic images

and is more consistent with human visual systems.

关键词

Keywords

references

李艳,苏萍,马建设,等. 立体投影质量的评价方法及系统 [J]. 液晶与显示, 2012, 27(1): 31-37. LI Y, SU P, MA J SH, et al.. Evaluation method and system of stereoscopic projection quality [J]. Chinese Journal of Liquid Crystals and Displays, 2012, 27(1):31-37. (in Chinese)

李小方,王琼华,李大海,等. 自由立体显示器观看视疲劳 [J]. 液晶与显示, 2008, 23(4): 464-467. LI X F, WANG Q H, LI D H, et al.. Viewer’s visual fatigue in autostereoscopic display [J]. Chinese Journal of Liquid Crystals and Displays, 2008, 23(4):464-467. (in Chinese)

LAMBOOIJ M, IJSSELSTEIJN W A, FORTUIN M, et al.. Visual discomfort and visual fatigue of stereoscopic displays: a review [J]. Journal of Imaging Science and Technology, 2009, 53(3):1-14.

TAM W J, SPERANZA F, YANO S, et al.. Stereoscopic 3D-TV: Visual comfort [J]. IEEE Transactions on Broadcasting, 2012, 57(2): 335-346.

范媛媛,沈湘衡,桑英军. 基于对比度敏感度的无参考图像清晰度评价 [J]. 光学精密工程, 2011, 19(10): 2485-2493. FAN Y Y, SHEN X H, SANG Y J. No reference image sharpness assessment based on contrast sensitivity [J]. Opt. Precision Eng., 2011, 19(10): 2485-2493. (in Chinese)

袁飞,黄连芬,姚彦. 基于视觉掩盖效应和奇异值分解的图像质量评测方法 [J]. 光学精密工程,2008,16(4): 706-713. YUNA F, HUANG L F, YAO Y. Image quality evaluation based on visual masking effect and singular value decomposition [J]. Opt. Precision Eng., 2008, 16(4): 706-713. (in Chinese)

郁梅,孔真真,朱江英. 基于视觉阈值及通道融合的立体图像质量评价[J]. 光学精密工程,2013,21(6): 1605-1612. YU M, KONG ZH ZH, ZHU J Y. Stereoscopic image quality assessment based on visual threshold and channel fusion [J]. Opt. Precision Eng., 2013, 21(6): 1605-1612. (in Chinese)

CHOI J, KIM D, HAM B, et al.. Visual fatigue evaluation and enhancement for 2D-plus-depth video [C]. 2010 17th IEEE International Conference on Image Processing (ICIP2010), 2010: 2981-2984.

LAMBOOIJ M, IJSSELSTEIJN W A, HEYNDERICKX I. Visual discomfort of 3-D TV: Assessment methods and modeling [J]. Displays, 2012, 32(4): 209-218.

ITTI L, KOCH C, NIEBUR E. A model of saliency-based visual attention for rapid scene analysis [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998, 20(11): 1254-1259.

HOU X, ZHANG L. Saliency detection: A spectral residual approach [C]. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR2007), 2007: 1-8.

BRUCE N, TSOTSOS J. Saliency based on information maximization [C]. Advance in Neural Information Processing Systems (NIPS2006), 2006: 155-162.

ZHAO Q, KOCH C. Learning visual saliency by combining feature maps in a nonlinear manner using AdaBoost [J]. Journal of Vision, 2012, 12(6): 22, 1-15.

ERDEM E, ERDEM A. Visual saliency estimation by nonlinearly integrating features using region covariance [J]. Journal of Vision, 2013, 13(4): 11, 1-20.

LANG C Y, NGUYEN T V, KATTI H, et al.. Depth matters: influence of depth cues on visual saliency [C]. 12th European Conference on Computer Vision (ECCV2012), Florence, Italy, 2012: 101-115.

TUZEL O, PORIKLI F, MEER P. Region covariance: A fast descriptor for detection and classification [C]. In European Conference of Computer Vision (ECCV 2006), Series: Lecture Notes in Computer Science (3952), Berlin, 2006: 589-600.

HONG X P, CHANG H, SHAN SH G, et al.. Sigma set: A small second order statistical region descriptor [C]. IEEE Conference on Computer Vision and Pattern Recognition (CVPR2009), 2009:1802-1809.

KIM J S, SIM J Y, KIM CH S. Multiscale saliency detection using random walk with restart [J]. IEEE Transactions on Circuits and Systems for Video Technology, 2013,24(2):198-210.

ZHANG L, GU ZH Y, LI H Y. SDSP: A novel saliency detection method by combining simple priors [C]. 2013 IEEE International Conference on Image Processing (ICIP2013), Session: Visual Attention and Saliency, Melbourne, Australia, 2013.

BROOKES A, STEVENS K. The analogy between stereo depth and brightness [J]. Perception, 1989, 18(5): 601-614.

WANG J L, SILVA M P D, CALLET P L, et al.. A computational model of stereoscopic 3D visual saliency [J]. IEEE Transactions on Image Processing, 2013, 22(6): 2151-2165.

ZHANG X G. Introduction to statistical learning theory and support vector machines[J]. Acta Automation Sinica, 2000, 26(1):32-41.

IVY Lab stereoscopic image database [OL]. [2013-03-12]. http://ivylab.kaist.ac.kr/demo/3DVCA/3DVCA.htm.

Views

220

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Compressive tracking algorithm combining online feature selection with covariance matrix

Stereoscopic image quality Assessment based on visual threshold and channel fusion

Assessment of storage reliability for FOGs by multivariate degradation data

2-D attitude measurement of object based on covariance matrix

The Characteristic Properties Analysis for Multispectral Data Compression Based on Karhunen-Leove Transformation

Related Author

Hong-ying ZHANG

Can-feng LI

KONG Zhen-zhen

ZHU Jiang-ying

CHAO Dai-hong

MA Jing

CHEN Shu-ying

纪华

Related Institution

College of Electronic Information and Automation, Civil Aviation University of China

北京航空航天大学仪器科学与光电工程学院

中国科学院长春光学精密机械与物理研究所2. 中国科学院长春光学机密机械与物理研究所3. 中国科学院长春光学精密机械与物理研究所4. 中科院长春光机所

Dept.of Communication engineerings, Changchun Institute of Posts & Telecommunication

Changchun Institute of Optics & Fine Mechanics, Chinese Academy of Sciences

AI问答

Address：No.3888 Dong Nanhu Road, Changchun, Jilin, China Postal code：130033
Tel：0431-86176855 Email：gxjmgc@ciomp.ac.cn
Technical support is provided by Beijing Founder electronics co., LTD 吉ICP备11002662号-17 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰