CRII: RI: Sub-mm 3D Scanning of Real-World Scenes with Active Multi-View Event Sensing

CRII：RI：通过主动多视图事件传感对现实世界场景进行亚毫米 3D 扫描

• 批准号: 2328619
• 负责人: Florian Willomitzer
• 金额: $ 17.5万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2328619&HistoricalAwards=false
• 关键词: CRII; RI; Sub; mm; 3D

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).State-of-the-art 3D imaging methods are not able to measure all possible classes of objects at once and still need to be tailored to a specific application. This is one of the main reasons why 3D imaging is still not omnipresent in our society, and still solely trained experts with task-specific equipment are able to capture high-quality 3D models. This project seeks to build a “one fits all” system that has the potential to change this. The targeted system enables precise 3D measurements of complicated surfaces/scenes in today’s billion-dollar industries, such as virtual reality, industrial inspection, autonomous navigation, or medical imaging. Many of these industries routinely run into particularly challenging scenarios for 3D scanning systems. Moreover, a scene-independent and precise 3D sensing system can have many applications. The produced sets of high-quality 3D data can usher the next wave in vision-related artificial intelligence research, leading to algorithms with unprecedented detection quality, prediction accuracy, or navigation precision. Given the current dissimilation of related techniques in all sectors of our modern society, everyone can profit. The project is accompanied by a comprehensive education program incorporating 3D imaging principles in a curriculum for Chicago afterschool programs to introduce at-risk youth to basic concepts in optics, image processing, and electronics.The focus of this research is to solve a long-standing problem in Computer Vision: high-resolution active 3D scanning of scenes cluttered with objects of mixed specularity and polluted by undesirable light contributions such as ambient illumination or strong inter-reflections. Existing approaches for this challenging task deliver rather sobering results or rely on large training datasets or other extensive prior knowledge, such as the geometry and reflectance of objects in the scene. An easy and flexible solution that delivers high-quality data is of significant interest for researchers in the broader computer vision community. This research distills the past decade’s research of the investigator and his colleagues. It combines previous experience in active multi-view 3D imaging concepts for different object classes with the novel detection modality of biologically inspired event sensors (which operate on a fundamentally different principle than conventional sensors). By properly facilitating the existing tradeoffs in 3D imaging and event sensing, the team will develop theory, hardware, and algorithms that lead to a fundamentally new type of 3D camera. The developed technique significantly advances the state-of-the-art and our fundamental understanding of limits.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.

该奖项的全部或部分资金来源于《2021 年美国救援计划法案》（公法 117-2）。最先进的 3D 成像方法无法同时测量所有可能类别的物体，但仍然需要这是 3D 成像在我们的社会中仍然不普遍的主要原因之一，并且仍然只有经过培训的专家拥有特定任务的设备才能捕获高质量的 3D 模型。建造“一应俱全”的系统有可能改变这一现状，目标系统可以对当今价值数十亿美元的行业（例如虚拟现实、工业检测、自主导航或医学成像）中的复杂表面/场景进行精确的 3D 测量。这些行业经常遇到 3D 扫描系统特别具有挑战性的场景，此外，独立于场景的精确 3D 传感系统可以有许多应用，所生成的高质量 3D 数据集可以引领视觉相关人工智能的下一波浪潮。研究，导致鉴于当前现代社会各个领域相关技术的差异，每个人都可以受益于芝加哥课程中包含 3D 成像原理的综合教育计划。这项研究的重点是解决计算机视觉中长期存在的问题：对充满混合物体的场景进行高分辨率主动 3D 扫描镜面反射度和受到不良光影响（例如环境照明或强烈的相互反射）的影响，这项具有挑战性的任务的现有方法提供了相当清醒的结果，或者依赖于大型训练数据集或其他广泛的先验知识，例如场景中物体的几何形状和反射率。提供高质量数据的简单灵活的解决方案引起了更广泛的计算机视觉社区的研究人员的极大兴趣。这项研究总结了研究人员及其同事过去十年的研究成果，它结合了主动多视图 3D 成像概念的经验。通过受生物启发的事件传感器的新颖检测方式（其工作原理与传统传感器完全不同），针对不同的物体类别，通过适当促进 3D 成像和事件传感中的现有权衡，该团队将开发理论、硬件和算法。所开发的技术进步显着地反映了最先进的技术和我们对极限的基本理解。该奖项是 NSF 的法定使命，并且通过使用基金会的知识进行评估，被认为值得支持。优点和更广泛的影响审查标准。