论文标题
通过深度学习，非线视线成像从phong表面脱颖而出
Non-line-of-sight imaging off a Phong surface through deep learning
论文作者
论文摘要
开发了基于深度学习的非视线（NLOS）成像系统，以对散射表面的遮挡对象进行成像。神经网仅使用手写数字进行训练，但具有重建与训练集不同的模式（包括物理对象）的能力。它还可以实时从其散射模式中重建卡通视频，以证明基于深度学习的方法的鲁棒性和概括能力。通过实验检查了几个具有不同程度的兰伯特和镜面贡献的散射表面。已经发现，对于兰伯特表面，重建图像的结构相似性指数（SSIM）约为0.63，而从拥有镜面分量的散射表面获得的SSIM可以高达0.93。根据phong散射模型开发了光传输的正向模型。通过数值模拟了不同程度的镜面贡献的Phong表面的散射模式。发现与实验数据的结果一致，较小的5％的镜面贡献可以将SSIM从0.83提高到0.93。计算各种phong表面的基础转移矩阵的奇异值光谱。 As the weight and the shininess factor increase, i.e., the specular contribution increases, the singular value spectrum broadens and the 50-dB bandwidth is increased by more than 4X with a 10% specular contribution, which indicates that at the presence of even a small amount of specular contribution the NLOS measurement can retain significantly more singular value components, leading to higher reconstruction fidelity.借助普通的摄像头和不连贯的光源，这项工作可以实现低成本的实时NLOS成像系统，而无需明确的基础光传输过程的物理模型。
A deep learning based non-line-of-sight (NLOS) imaging system is developed to image an occluded object off a scattering surface. The neural net is trained using only handwritten digits, and yet exhibits capability to reconstruct patterns distinct from the training set, including physical objects. It can also reconstruct a cartoon video from its scattering patterns in real time, demonstrating the robustness and generalization capability of the deep learning based approach. Several scattering surfaces with varying degree of Lambertian and specular contributions were examined experimentally; it is found that for a Lambertian surface the structural similarity index (SSIM) of reconstructed images is about 0.63, while the SSIM obtained from a scattering surface possessing a specular component can be as high as 0.93. A forward model of light transport was developed based on the Phong scattering model. Scattering patterns from Phong surfaces with different degrees of specular contribution were numerically simulated. It is found that a specular contribution of as small as 5% can enhance the SSIM from 0.83 to 0.93, consistent with the results from experimental data. Singular value spectra of the underlying transfer matrix were calculated for various Phong surfaces. As the weight and the shininess factor increase, i.e., the specular contribution increases, the singular value spectrum broadens and the 50-dB bandwidth is increased by more than 4X with a 10% specular contribution, which indicates that at the presence of even a small amount of specular contribution the NLOS measurement can retain significantly more singular value components, leading to higher reconstruction fidelity. With an ordinary camera and incoherent light source, this work enables a low-cost, real-time NLOS imaging system without the need of an explicit physical model of the underlying light transport process.
