Feel3D: Free Viewpoint Video Recording Mechanism for Premeditated Scenarios, Using Pre-built Models

B. N. Wickramasinghe, N. Kodikara
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Abstract

Current Free Viewpoint Video making methods depends on real-time video footage to synthesize new views or apply texture on models in the video. This approach faces challenges in producing structurally and textually correct views when video recording conditions change. This project focuses on using pre-built 3D models for FVV making. As opposed to conventional FVV making methods, proposed approach will produce better quality 3D FVV with less processing. Furthermore, the project will introduce a new framework for 3D free viewpoint videos. The 3D FVVs made with the proposed approach will allow efficient storage and frugal bandwidth usage during transmission. Following sections will present about employed motion tracking method, use of 3D models and how all the parts are combined to produce the free viewpoint video. The latter stages will discuss strengths and limitations as well as the effect of this approach on commercial and research interests related to FVVs.
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Feel3D:免费视点视频记录机制为预先考虑的场景,使用预建模型
当前的免费视点视频制作方法依赖于实时视频素材来合成新的视图或在视频模型上应用纹理。当视频录制条件发生变化时,这种方法在生成结构和文本正确的视图方面面临挑战。这个项目的重点是使用预先建立的3D模型的FVV制作。与传统的FVV制作方法相比,该方法可以以较少的加工产生更高质量的3D FVV。此外,该项目将引入3D免费视点视频的新框架。采用该方法制作的3D fvv将在传输过程中实现高效存储和节省带宽使用。以下各节将介绍所采用的运动跟踪方法,使用3D模型以及如何将所有部件组合在一起以产生免费的视点视频。后一阶段将讨论这种方法的优势和局限性,以及对与FVVs相关的商业和研究兴趣的影响。
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