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Hybrid 3D Reconstruction for Geometry-Based Free Viewpoint Video

基于几何的自由视点视频的混合 3D 重建

基本信息

批准号：
232339705
负责人：
Professor Dr.-Ing. Thomas Sikora
金额：
--
依托单位：
Fachgebiet Nachrichtenübertragung
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2013
资助国家：
德国
起止时间：
2012-12-31 至 2015-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/232339705?language=en
关键词：
Hybrid 3D Reconstruction Geometry Based

项目摘要

Our purpose is to develop algorithms for capturing time-varying 3D scene geometry in the context of Free Viewpoint Video applications. This requires a large working volume of at least 2.5m x 2.5m x 3m for capturing a scene. Our strategy involves the generation of a 3D computer graphics model from the captured scene geometry. This model is used at the receiver to reconstruct full parallax Free Viewpoint stereoscopic video. In order to display the time- and view-varying 3D content of the scene on stereoscopic or multi-view displays, it is important that solutions are real-time capable and allow capture of 3D computer graphics models that are as complete and as accurate as possible. Our research strategy attempts to overcome limitations of active and passive techniques for image reconstruction by combining information from both techniques in a hybrid sensor fusion approach. To this end, we employ a multi-projector multi-camera system to project structured light onto the scene and a phase-shifting technique to extract depth and texture information in an active vision approach. The passive multi-camera system is then used to arrive at additional disparity information, which will improve depth and texture reconstruction of the 3D scene model. In order to reduce texture dependent artifacts that stem from large aperture cameras we will derive deconvolution algorithms that use the inverse of an estimated spatially varying point-spread function.

我们的目的是开发算法捕捉时变的3D场景几何在自由视点视频应用程序的上下文中。这需要至少2.5m x 2.5m x 3m的大工作体积来捕捉一个场景。我们的策略包括从捕获的场景几何图形生成3D计算机图形模型。该模型用于接收端重建全视差无视点立体视频。为了在立体或多视图显示器上显示场景的时间和视图变化的3D内容，重要的是解决方案具有实时能力，并允许捕获尽可能完整和准确的3D计算机图形模型。我们的研究策略试图通过在混合传感器融合方法中结合两种技术的信息来克服主动和被动图像重建技术的局限性。为此，我们采用多投影仪多摄像机系统将结构光投射到场景中，并采用相移技术在主动视觉方法中提取深度和纹理信息。然后利用被动多相机系统获得额外的视差信息，从而改善三维场景模型的深度和纹理重建。为了减少源于大孔径相机的纹理相关伪影，我们将推导使用估计的空间变化点扩展函数的逆卷积算法。