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Visual Comfort Assessment Metric Based on Motion Features in Salient Motion Regions for Stereoscopic 3D Video

Conference paper
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Part of the Communications in Computer and Information Science book series (CCIS, volume 331)

Abstract

Visual comfort assessment for stereoscopic 3D video is of great importance for stereoscopic safety and health issue. In order to investigate visual discomfort induced by motion features in salient motion regions, we propose a visual comfort assessment metric that focuses on pixel-level motion features in salient motion regions. In our framework, we propose the pixel-level motion features extraction method based on point detector, Kanade-Lucas-Tomasi(KLT) feature tracker, and Salient Motion Depth Extraction (SMDE) approach. The motion features are spatially pooled and temporally pooled to predict visual comfort score. Subjective assessments have been conducted to evaluate our proposed visual comfort metric using natural stereoscopic videos. The experiment results have been demonstrated that our proposed visual comfort metric improves the correlation with subjective assessments.

Keywords

visual comfort assessment point detector KLT feature tracker SMDE approach 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Institute of Image Communication and Information ProcessingShanghai Jiao Tong UniversityShanghaiChina
  2. 2.Shanghai Key Laboratory of Digital Media Processing and TransmissionsShanghai Jiao Tong UniversityShanghaiChina

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