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In this paper, we propose a framework for clustering shots from stereoscopic videos into clusters that correspond to semantic concepts exploiting visual and disparity information. Various color, disparity and texture descriptors are applied to shot key frames for obtaining low-level representations. Self Organizing Maps are subsequently employed upon various combinations of these representations in...
In this paper we propose a framework for stereoscopic video shot classification that includes low-level representations exploiting visual and disparity information and determination of optimal discriminant subspaces based on Linear Discriminant Analysis (LDA). Low-level representations are obtained through various color, disparity and texture descriptors which are applied to shot key frames. A new...
3DTV and 3D cinema have become quite popular during the last few years. It is now well understood that certain 3D video quality issues may have a negative effect in the 3D viewing experience. In this paper, we propose two novel algorithms that exploit available disparity information, in order to detect two disturbing stereoscopic issues, namely Stereoscopic Window Violations (SWV) and bent window...
3DTV and 3D cinema witness a significant increase in their popularity nowadays. New movie titles are released in 3D and there are more than 35 TV channels in various countries that broadcast in 3D worldwide. It is well known today and becomes more obvious, as the 3D video content availability increases, that stereoscopy is associated with certain 3D video quality issues that may affect in a negative...
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