Stereoscopic 3D quality analyzer and advanced depth control

2010 . 01 ~ current

 

1. Introduction

n  Although the interest of 3D content service has increased, the lack of high quality 3D contents (e.g., without visual discomfort) has been still a relevant obstacle preventing the proliferation of stereoscopic 3D services into the mass market.

n  Techniques that analyze and ameliorate the visual discomfort of 3D contents could enable to produce high quality 3D contents and to reuse ordinary contents. Hence, the technique can be one of solution to the lack of high quality 3D contents.

n  The developed 3D quality analyzer presents the results of video quality analysis according to various visual discomfort causes. Also, the advanced depth controller enhances the visual comfort by automatic disparity control taking account to discomfort causes.

2. Method

Fig. 1. Overview of quality analyzer and quality enhancer for stereoscopic 3D video

2.1. 3D quality analyzer

n  Most of 3D quality analysis techniques are based on 2D quality analysis technique. Hence, these techniques are not proper to 3D quality since 3D quality of experience consists multiple factors such as visual discomfort, depth quality, picture quality and so on. In addition, previous techniques cannot provide the detailed analysis results that indicate the problematic discomfort cause, which leads to the increase of 3D contents production cost.

n  “3D Quality Analyzer” can provide the comfort analysis results with respect to various discomfort causes, and quantify the overall 3D quality.

Fig. 2. Overall process of “3D Quality Analyzer”

n  Demo video

2.2. Advanced depth controller

n  Most of conventional techniques for improving visual comfort use the global linear disparity adjustment, which could lead to the side effects such as the reduced depth impression and depth distortion due to excessive disparity adjustment.

n  “Advanced Depth Control” adaptively (linear/non-linear) adjusts the disparity of stereoscopic image according to discomfort causes based on the comfort analysis results in order to improve visual comfort.

Fig. 3. Example of “Advanced depth control”

n  Demo video

3. Applications

n  Smart stereo image analyzer to assist the production of high quality (i.e., comfortable) 3D movie and broadcasting contents

n  Best Comfort Shot 3D camera to automatically control the capturing of comfortable stereo image

n  Best Comfort Picture 3D display to automatically assess and reduce the visual discomfort

n  Comfortable 3D contents search/recommendation services based on the automatic classification of comfort

4. Status of intellectual property right

Type

Title

Application number
(Date of filing)

Patent number
(Date of publication)

Patent

스테레오스코픽 이미지 영상의 시각 피로도를 시각화하는 장치 방법

 

10-1356427
(2014-01-22)

Patent

스테레오스코픽 영상 시스템에서의 시각적 불편감 측정 장치 방법, 시각적 불편감 측정 방법을 실행하기 위한 프로그램이 기록된 기록매체

 

10-1220223
(2013-01-03)

Patent

3D 영상의 시차 조절과 크로스톡 억제 기술을 결합한 3D 디스플레이의 시청 크로스톡 저감 방법

10-2014-0024866
(2014.03.03)

 

Patent

스테레오스코픽 3-D 디스플레이를 위한 시각적 편안함 향상 방법 장치

10-2014-0003749
(2014-01-13)

 

Patent

시각적으로 편안한 입체 영상을 위한 스테레오스코픽 영상 촬영 방법 시스템

10-2013-0071520
(2013-06-21)

 

Patent

Apparatus for Visualizing Visual Fatigue in Stereoscopic Image

PCT-KR2011-009932
(2011-12-21)

 

Software

스테레오스코픽 3D 비디오의 시각적 편안함 분석기

 

C-2014-010201
(2014-05-08)

Software

스테레오스코픽 3D 비디오의 시각적 편안함 향상기

 

C-2014-010202
(2014-05-08)

 

 

 

 

* Contact Person: Prof. Yong Man Ro (ymro@ee.kaist.ac.kr)

* Participant:

 

 Yong Ju Jung

yj.jung@kaist.ac.kr

 Research Associate Professor in Dept. of EE in KAIST

 

 

 

 Hosik Sohn

sohnhosik@kaist.ac.kr

  Ph.D in Dept. of EE in KAIST

Researcher in Samsung Electronics

 

 

 

 

 

설명: 설명: 설명: 설명: 설명: 설명: 설명: 설명: 설명: cid:image001.jpg@01CC0639.73E14F30

 Seong-il Lee

vitallsi@kaist.ac.kr

  Ph.D Candidate in Dept. of EE in KAIST

Researcher in IVY Lab in KAIST

 

 

 

 

 

Y. J. Jung, H. Sohn, S. Lee, and Y. M. Ro, “Visual comfort improvement in stereoscopic 3D displays using perceptually plausible assessment metric of visual comfort,” IEEE Transactions on Consumer Electronics, vol. 60, no. 1, pp. 1-9, 2014

S. Lee, Y. J. Jung, H. Sohn, and Y. M. Ro, “Experimental investigation of discomfort combination: Towards visual discomfort prediction for stereoscopic videos,” Journal of Electronic Imaging, vol. 23, no. 1, p. 011003, 2014

H. Sohn, Y. J. Jung, S. Lee, F. Speranza, and Y. M. Ro, Visual comfort amelioration technique for stereoscopic image: Disparity remapping to mitigate global and local discomfort causes, IEEE Transactions on Circuits and Systems for Video Technology, vol. 24, no. 5, pp. 745-758, 2014.

Y. J. Jung, H. Sohn, S. Lee, H. W. Park, and Y. M. Ro, Predicting visual discomfort of stereoscopic images using human attention model, IEEE Transactions on Circuits and Systems for Video Technology, vol. 23, no. 12, pp. 2077-2082, 2013.

H. Sohn, Y. J. Jung, S. Lee, and Y. M. Ro, Predicting visual discomfort using object size and disparity information in stereoscopic images, IEEE Transactions on Broadcasting, vol. 59, no. 1, pp. 28-37, 2013.

Y. J. Jung, S. Lee, H. Sohn, H. W. Park, and Y. M. Ro, Visual comfort assessment metric based on salient object motion information in stereoscopic video, Journal of Electronic Imaging, Vol. 21, No. 1, p. 011008, 2012.