Collaborative Research: CIF: Medium: Occlusion and Directional Resolution in Computational Imaging

合作研究：CIF：媒介：计算成像中的遮挡和方向分辨率

• 批准号: 1955219
• 负责人: Vivek Goyal
• 金额: $ 60万
• 依托单位: Trustees of Boston University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1955219&HistoricalAwards=false
• 关键词: Collaborative; Research; CIF; Medium; Occlusion

Seeing around a corner without using a mirror seems like an impossible feat, and an ordinary camera does not seem to help. In this project, the research team will develop systems to process images and videos from ordinary cameras to construct around-the-corner views and to infer other scene features that are hidden from direct view such as the numbers of people present. The team will also augment the use of ordinary cameras with depth sensors such as those used in self-driving cars and immersive gaming. Being able to see around corners has the potential to aid first responders and improve navigation safety. The fundamental difficulty in using diffusely reflected light in imaging is that light from many directions is combined at the visible surface. Methods for non-line-of-sight imaging have predominantly depended on separating light paths by their lengths using expensive, high-resolution time-of-flight (TOF) measurement. Instead of depending entirely on TOF, this project emphasizes the exploitation of opaque objects that create restrictions and variations in how light is combined at a diffuse surface. The research team will also develop a framework to express inverse problem difficulty that goes beyond condition numbers to provide localized and directional concepts for resolution. Analyses will inspire and be informed by proof-of-concept experiments.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.

不用镜子看一个角落似乎是不可能的壮举，而普通的相机似乎也没有帮助。在这个项目中，研究团队将开发系统来处理来自普通摄像机的图像和视频，以构建拐角处的视图，并推断其他隐藏在直接视图之外的场景特征，例如在场的人数。该团队还将在自动驾驶汽车和沉浸式游戏中使用的深度传感器中增加普通相机的使用。能够看到拐角处有可能帮助急救人员并提高导航安全性。在成像中使用漫反射光的根本困难是来自多个方向的光在可见表面上组合在一起。非视距成像的方法主要依赖于使用昂贵的、高分辨率的飞行时间（TOF）测量方法根据光路的长度来分离光路。这个项目不是完全依赖于TOF，而是强调利用不透明的物体，这些物体会在漫射表面上产生光线组合的限制和变化。研究小组还将开发一个框架来表达超越条件数的反问题难度，为解决提供局部和定向的概念。分析将受到概念验证实验的启发和启发。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Dithered depth imaging

抖动深度成像

• DOI: 10.1364/oe.408800
• 发表时间: 2020
• 期刊: Optics Express
• 影响因子: 3.8
• 作者: Rapp, Joshua;Dawson, Robin M. A.;Goyal, Vivek K.
• 通讯作者: Goyal, Vivek K.

Fast Computational Periscopy in Challenging Ambient Light Conditions through Optimized Preconditioning

通过优化预处理在具有挑战性的环境光条件下快速计算潜望镜

• DOI: 10.1109/iccp51581.2021.9466264
• 发表时间: 2021
• 期刊: Proc. IEEE Int. Conf. Computational Photography
• 作者: Saunders, Charles;Goyal, Vivek K
• 通讯作者: Goyal, Vivek K

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

• DOI: 10.1109/tci.2020.3037405
• 发表时间: 2021-01-01
• 期刊: IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING
• 影响因子: 5.4
• 作者: Seidel, Sheila W.;Murray-Bruce, John;Goyal, Vivek K.
• 通讯作者: Goyal, Vivek K.

MEGS: A Penalty for Mutually Exclusive Group Sparsity

• DOI: 10.1109/ojsp.2023.3271249
• 发表时间: 2023
• 期刊: IEEE Open Journal of Signal Processing
• 影响因子: 2.8
• 作者: Charles Saunders;V. K. Goyal

Edge-Resolved Transient Imaging: Performance Analyses, Optimizations, and Simulations

边缘分辨瞬态成像：性能分析、优化和模拟

• DOI: 10.1109/icip42928.2021.9506590
• 发表时间: 2021
• 期刊: IEEE International Conference on Image Processing (ICIP
• 作者: Saunders, Charles;Krska, William;Tachella, Julian;Seidel, Sheila W.;Rapp, Joshua;Murray-Bruce, John;Altmann, Yoann;McLaughlin, Stephen;Goyal, Vivek K
• 通讯作者: Goyal, Vivek K