2010 IEEE International Conference on Image Processing 2010
DOI: 10.1109/icip.2010.5651142
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Temporal synchronization in stereoscopic video: Influence on quality of experience and automatic asynchrony detection

Abstract: In this paper, we analyze the influence of temporal asynchrony on the subjective quality of stereoscopic video. Based on our recently created 3D video database, different levels of asynchrony were simulated and a comprehensive subjective test was conducted to determine the associated degradations in quality of experience. Furthermore, we developed a method to detect asynchrony between left and right video streams based on canonical correlation analysis. Experiments demonstrate the robustness of this method wit… Show more

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Cited by 21 publications
(5 citation statements)
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“…For (intra-media) synchronization quality of 3D stereoscopic videos, Goldmann et al [2010] evaluate four video samples with different scenes, all at a frame rate of 25 fps and a spatial resolution of 1920x1080. The authors claim that a skew below 80 ms leads to a good 3D visual quality, while a skew larger than 200 ms annoys the visual experience.…”
Section: Synchronization Perception Of New Mediamentioning
confidence: 99%
“…For (intra-media) synchronization quality of 3D stereoscopic videos, Goldmann et al [2010] evaluate four video samples with different scenes, all at a frame rate of 25 fps and a spatial resolution of 1920x1080. The authors claim that a skew below 80 ms leads to a good 3D visual quality, while a skew larger than 200 ms annoys the visual experience.…”
Section: Synchronization Perception Of New Mediamentioning
confidence: 99%
“…The researchers have studied the influence of temporal asynchrony on the subjective quality and found that an offset of more than 2 frames leads to a significant quality drop [2]. Another study addressed the problem of understanding the effect of brightness on the visual comfort and quality of 3D videos and observed that the quality increases as the brightness increases [3].…”
Section: Introductionmentioning
confidence: 97%
“…Various 3D experiments demonstrate the effectiveness of the proposed method. [1] . 대표적으로 콘텐츠 자체를 분석해서 동기 오류를 검출하는 방법 [2] 으로 좌-우 영상의 시퀸스를 분석하 고, 두 영상 시퀀스에서 검출된 2D 특징 불변점들을 활용하 여 Dynamic Programming 기법을 통한 동기 오류를 검출하 는 방법을 제안하였다.…”
Section: Introductionunclassified
“…대표적으로 콘텐츠 자체를 분석해서 동기 오류를 검출하는 방법 [2] 으로 좌-우 영상의 시퀸스를 분석하 고, 두 영상 시퀀스에서 검출된 2D 특징 불변점들을 활용하 여 Dynamic Programming 기법을 통한 동기 오류를 검출하 는 방법을 제안하였다. 그리고 L. Goldmann 외 2명이 제안 한 논문에서는 CCA(Canonical Correlation Analysis)를 이 용한 방법이 소개되었다 [1] . 여기서는 동영상을 시간별로, 공간별로 분할한 뒤 각 타일의 매칭을 통해 동기 오류를 구하는 방법을 제안하며 시간적 동기가 맞지 않을 경우 스 테레오 영상 품질이 얼마나 달라지는가를 실험적 방법을 통해 제시하고 있다 [1,3] .…”
Section: Introductionunclassified
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