SBIR Phase II: Fast Creation of Photorealistic 3D Models using Consumer Hardware

这个小企业创新研究（SBIR）第二阶段项目的更广泛的影响/商业潜力将是巨大的：一个成功的项目将改变建筑行业，通过减少法律的冲突，进度表和决策失误，使其更加有效。拟议的工作将能够快速轻松地创建物理空间的100%完整的视觉文档;该文档可以在整个施工过程中多次生成。通过这样做，拟议的项目将允许建筑行业的专业人士跟踪进度，并比以往任何时候都更有效地与他们的团队进行沟通。该项目的第二个成果将是创建庞大、详细、前所未有的建筑项目和真实的房地产数据集，使人工智能和计算机视觉的技术创新能够影响美国乃至世界上最大的行业之一。例如，可以训练系统自动发现安全问题，增强安全管理人员的努力，并使工人比以往任何时候都更安全。这个小型企业创新研究（SBIR）第二阶段项目将开发一种快速，易于使用和廉价的方法，使用现成的消费硬件创建逼真的沉浸式模型。技术障碍包括验证使用消费者硬件生成的模型的质量和有效性，以及在没有人工注释的情况下自动创建通过3D空间的路线。技术里程碑涉及使用各种传感器流以及其他先前数据来构建这些路线。随着这些障碍的清除，高级工作可能包括随着时间的推移捕获的同一站点的3D模型之间的自动分析。由于该系统的易用性，它将使收集大型，全新的数据集。这项研究的目标是产生一个原型，外行可以用来创建一个物理站点的沉浸式模型，以便在没有注释的情况下记录它。实现这些目标的计划包括针对上述障碍的迭代软件开发，以及持续的用户反馈，以指导和完善开发。该奖项反映了NSF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。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will be substantial: a successful project would transform the construction industry, making it far more efficient by reducing legal conflicts, schedule slips and poor decision making. The proposed work will enable the fast and easy creation of 100% complete visual documentation of a physical space; this documentation can be generated many times throughout the course of construction. In so doing, the proposed project will allow professionals in the construction industry to track progress and communicate with their teams far more efficiently than ever before. A second outcome of the project will be the creation of vast, detailed, never before seen datasets of construction projects and real estate, allowing technical innovations in artificial intelligence and computer vision to impact one of the largest industries in the nation and the world. For example, systems could be trained to automatically spot safety concerns, augmenting the efforts of safety managers and keeping workers safer than ever before.This Small Business Innovation Research (SBIR) Phase II project will develop a fast, easy to use and cheap method to create photorealistic immersive models using off the shelf consumer hardware. Technical hurdles include validating the quality and efficacy of models generated with consumer hardware and automatic creation of routes through the 3D space without human annotation. Technical milestones involve using various sensor streams as well as other prior data to build these routes. With these hurdles cleared, advanced work may include automated analytics between and among 3D models of the same site captured over time. Because of the system's ease of use, it will enable the collection of large, totally novel datasets. The goal of the research is to produce a prototype that a layperson can use to create an immersive model of a physical site in order to document it with no annotation effort. The plan to reach these goals includes iterative software development against the hurdles listed above, as well as continuous user feedback to guide and refine development.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.