RI: Small: Collaborative Research: Dynamic Light Transport Acquisition and Applications to Computational Illumination

RI：小型：合作研究：动态光传输采集及其在计算照明中的应用

• 批准号: 1909192
• 负责人: Suren Jayasuriya
• 金额: $ 25万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-15 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1909192&HistoricalAwards=false
• 关键词: RI; Small; Collaborative; Research; Dynamic

Cameras that view a dynamic scene typically capture interactions of moving objects with light. Computer vision algorithms can use these measurements to infer properties of these objects, such as depth, motion and appearance. However, there is a subtler, richer visual back-story that occurs as an object moves in a scene, and usually these effects are ignored in traditional algorithms, sometimes causing errors. This project studies all the interactions of light with dynamic scenes, which we term as dynamic light transport, and the goal is to understand and recover effects such as multiple reflections and scattering as objects move in a scene. The innovations of the project include new computational cameras and projectors to capture light transport for dynamic scenes, and to explore new physics-based and data-driven algorithms to exploit this information for improved computer vision and graphics applications. The project further seeks to include broadening access to computing education and research through curriculum material and capstone experiences which emphasize the intersection of light transport and digital media as well as outreach to middle and high school students in summer programs to discover imaging and optics applications.This research focuses on designing new light transport acquisition frameworks to capture dynamic scenes, characterization of dynamic light transport properties including sparsity and low-rank, and algorithms to exploit this information for computer vision applications. In particular, the project focuses on three main objectives. The first is design of an MEMs-based optical scanner coupled with high frame rate cameras to capture the full set of light transport paths at extremely fast timescales. The second contribution is new algorithms for adaptive light transport sampling using both physics-based and data-driven priors for light transport interpolation via generalized light transport flow. Finally, the project will provide applications of dynamic light transport for 3D scanning of deformable, moving, and specular objects. These innovations are evaluated in an integrated testbed via the optical scanner and the collection of a dataset of dynamic light transport for real-world scenes.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

查看动态场景的相机通常会捕捉移动物体与光的相互作用。计算机视觉算法可以使用这些测量来推断这些对象的属性，例如深度、运动和外观。然而，当物体在场景中移动时，会出现更微妙、更丰富的视觉背景故事，而传统算法通常会忽略这些效果，有时会导致错误。该项目研究光与动态场景的所有相互作用，我们将其称为动态光传输，目标是理解和恢复物体在场景中移动时的多次反射和散射等效果。该项目的创新包括新的计算相机和投影仪，用于捕获动态场景的光传输，并探索新的基于物理和数据驱动的算法，以利用这些信息来改进计算机视觉和图形应用。该项目进一步寻求通过课程材料和顶点体验扩大计算教育和研究的范围，强调光传输和数字媒体的交叉，以及在暑期课程中向中学生和高中生推广，以发现成像和光学应用。研究重点是设计新的光传输采集框架来捕获动态场景、动态光传输属性（包括稀疏性和低秩）的表征，以及利用这些信息进行计算机视觉应用的算法。该项目特别注重三个主要目标。 第一个是设计基于 MEM 的光学扫描仪，与高帧率相机相结合，以极快的时间尺度捕获全套光传输路径。 第二个贡献是自适应光传输采样的新算法，使用基于物理和数据驱动的先验通过广义光传输流进行光传输插值。 最后，该项目将为可变形、移动和镜面物体的 3D 扫描提供动态光传输的应用。这些创新通过光学扫描仪和收集真实世界场景的动态光传输数据集在集成测试台中进行评估。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优势和更广泛的评估进行评估，被认为值得支持。影响审查标准。

项目成果

Event-based dual photography for transparent scene reconstruction

基于事件的双重摄影，用于透明场景重建

• DOI: 10.1364/ol.483047
• 发表时间: 2023-02
• 期刊: Optics Letters
• 影响因子: 3.6
• 作者: Liu, Xiaomeng;Rego, Joshua D.;Jayasuriya, Suren;Koppal, Sanjeev J.
• 通讯作者: Koppal, Sanjeev J.

Programmable Non-Epipolar Indirect Light Transport: Capture and Analysis

可编程非极间接光传输：捕获和分析

• DOI: 10.1109/tvcg.2019.2946812
• 发表时间: 2021-04
• 期刊: IEEE Transactions on Visualization and Computer Graphics
• 影响因子: 5.2
• 作者: Kubo, Hiroyuki;Jayasuriya, Suren;Iwaguchi, Takafumi;Funatomi, Takuya;Mukaigawa, Yasuhiro;Narasimhan, Srinivasa G.
• 通讯作者: Narasimhan, Srinivasa G.

Dense Lissajous sampling and interpolation for dynamic light-transport

用于动态光传输的密集利萨如采样和插值

• DOI: 10.1364/oe.425061
• 发表时间: 2021-05
• 期刊: Optics Express
• 影响因子: 3.8
• 作者: Liu, Xiaomeng;Henderson, Kristofer;Rego, Joshua;Jayasuriya, Suren;Koppal, Sanjeev
• 通讯作者: Koppal, Sanjeev

Differentiable Programming for Hyperspectral Unmixing using a Physics-based Dispersion Model

使用基于物理的色散模型进行高光谱分解的可微分编程

• DOI: 10.1007/978-3-030-58583-9_39
• 发表时间: 2020-07-12
• 作者: J. Janiczek;Parth Thaker;Gautam Dasarathy;C. Edwards;P. Christensen;Suren Jayasuriya
• 通讯作者: Suren Jayasuriya

Slope Disparity Gating: System and Applications

斜率视差选通：系统和应用

• DOI: 10.1109/tci.2022.3162259
• 发表时间: 2022-01
• 期刊: IEEE Transactions on Computational Imaging
• 影响因子: 5.4
• 作者: Chandran, Sreenithy;Kubo, Hiroyuki;Ueda, Tomoki;Funatomi, Takuya;Mukaigawa, Yasuhiro;Jayasuriya, Suren
• 通讯作者: Jayasuriya, Suren