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arXiv 2006.09241eess.IVcs.CV
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从单个边缘遮挡物进行二维非视线场景估计

Two-Dimensional Non-Line-of-Sight Scene Estimation from a Single Edge Occluder

Sheila W. Seidel, John Murray-Bruce, Yanting Ma, Christopher Yu, William T. Freeman, Vivek K Goyal

AI总结:

本文提出了一种基于单张边缘遮挡物照片的二维非视线场景重建方法,通过改进的正向模型和两种反演算法实现了对隐藏场景的二维重建。

摘要:

被动非视线成像方法通常比主动方法更快且更隐蔽,需要更简单且成本更低的设备。然而,许多这些方法利用遮挡物或隐藏场景的运动,或需要对复杂的遮挡物进行知识或校准。墙的边缘是一种已知且普遍的遮挡结构,可以作为孔径来成像其后方的区域。从角落发出的光投射到地板上,形成扇形的半影而非锐利的阴影。半影中的细微变化包含大量关于隐藏场景的信息。先前的工作利用边缘的垂直性质,通过单张半影照片实现了对移动和静止隐藏场景的一维(以围绕角落的角度测量)重建。在本工作中,我们引入了第二个重建维度:从边缘测量的范围。我们推导出一个新的正向模型,考虑了径向衰减,并提出两种反演算法,从单张半影照片中形成二维重建。两种算法的性能在对应于几种不同隐藏场景配置的实验数据上得到了演示。Cramer-Rao界分析进一步证明了二维角落相机的可行性(和实用性)。

英文摘要:

Passive non-line-of-sight imaging methods are often faster and stealthier than their active counterparts, requiring less complex and costly equipment. However, many of these methods exploit motion of an occluder or the hidden scene, or require knowledge or calibration of complicated occluders. The edge of a wall is a known and ubiquitous occluding structure that may be used as an aperture to image the region hidden behind it. Light from around the corner is cast onto the floor forming a fan-like penumbra rather than a sharp shadow. Subtle variations in the penumbra contain a remarkable amount of information about the hidden scene. Previous work has leveraged the vertical nature of the edge to demonstrate 1D (in angle measured around the corner) reconstructions of moving and stationary hidden scenery from as little as a single photograph of the penumbra. In this work, we introduce a second reconstruction dimension: range measured from the edge. We derive a new forward model, accounting for radial falloff, and propose two inversion algorithms to form 2D reconstructions from a single photograph of the penumbra. Performances of both algorithms are demonstrated on experimental data corresponding to several different hidden scene configurations. A Cramer-Rao bound analysis further demonstrates the feasibility (and utility) of the 2D corner camera.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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