使用多相机流的3D头部重建

Donghoon Kim, Rozenn Dahyot
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引用次数: 3

摘要

给定来自许多摄像机的信息,人们可以希望得到一个物体的完整的3D表示。Pintavirooj和Sangworasil利用了这一想法,提出了一个系统,该系统从多个视点顺序记录图像,以重建感兴趣的静态物体的3D形状[1]。例如,在图像上使用60个视角,他们设法获得其精确的3D重建[1]。不幸的是,在考虑视频监控等应用时,指望60台摄像机同时提供一个嫌疑人的图像是不合理的。然而,我们可以预期,这个人会随着时间的推移而移动,并在至少一个或几个相机上显示她/他的头部的顺序不同的姿势。本文提出了一种通过组合不同时间记录的视图来恢复精确的3D形状的技术。
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3D Head Reconstruction Using Multi-camera Stream
Given information from many cameras, one can hope to get a complete 3D representation of an object. Pintavirooj and Sangworasil exploit this idea and present a system that records sequentially images from multiple view points to reconstruct a 3D shape of a static object of interest [1]. For instance, using a 60 angle of view on the image, they manage to get its accurate 3D reconstruction [1]. Unfortunately, when considering application such as video surveillance, it is not reasonable to expect that 60 cameras will give simultaneous images of a person of interest. However, we can expect that the person will move over time and show sequentially different poses of her/his head to at least one or a few cameras. This article proposes a technique for recovering an accurate 3D shape by combining views recorded at different times.
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