کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
529675 869693 2016 16 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Virtual view synthesis using layered depth image generation and depth-based inpainting for filling disocclusions and translucent disocclusions
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Virtual view synthesis using layered depth image generation and depth-based inpainting for filling disocclusions and translucent disocclusions
چکیده انگلیسی


• An occlusion layer plus depth image from single view plus depth is proposed to avoid disocclusion problems in virtual views.
• Translucent disocclusion problems are identified and handled by generating multiple occlusion layers.
• Proposed foreground-background classification and inpainting produces spatially consistent hole-filling.

View synthesis is an efficient solution to produce content for 3DTV and FTV. However, proper handling of the disocclusions is a major challenge in the view synthesis. Inpainting methods offer solutions for handling disocclusions, though limitations in foreground-background classification causes the holes to be filled with inconsistent textures. Moreover, the state-of-the art methods fail to identify and fill disocclusions in intermediate distances between foreground and background through which background may be visible in the virtual view (translucent disocclusions). Aiming at improved rendering quality, we introduce a layered depth image (LDI) in the original camera view, in which we identify and fill occluded background so that when the LDI data is rendered to a virtual view, no disocclusions appear but views with consistent data are produced also handling translucent disocclusions. Moreover, the proposed foreground-background classification and inpainting fills the disocclusions with neighboring background texture consistently. Based on the objective and subjective evaluations, the proposed method outperforms the state-of-the art methods at the disocclusions.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Visual Communication and Image Representation - Volume 38, July 2016, Pages 351–366
نویسندگان
, , ,