SBIR Phase I: Automatic Generation of As-Built BIM Models Using a Single Video Camera

小型企业创新研究(SBIR)第一阶段项目的更广泛影响/商业潜力是通过建筑信息建模(BIM)扫描和自动化的民主化来转变商业建筑。持续的设计和变更管理是一项独特的挑战，每年让美国建筑业损失数十亿美元。BIM通过促进早期分析和决策过程，显著降低了这些成本。现有的手工竣工BIM建模技术仅适用于大型商业建筑项目，因为该过程过于费力和昂贵；在小型项目中，预计节省的成本很难证明采用该过程是合理的。拟议的扫描到BIM技术有可能消除这些障碍。其易用性、减小的文件大小和自动化的对象检测支持更多扫描并创建更强大的数据模型，从而释放BIM流程的潜在潜力。这项技术提供的精简和数据管理能力可以产生巨大的价值，这些能力包括加快项目进度、减少对信息和变更单的要求以及及时发现设计冲突。通过启用支持自动BIM建模和有效基础设施管理的新服务，这为提高美国建筑业的竞争力铺平了道路。这个小型企业创新研究(SBIR)第一阶段项目将调查建筑业Scan-to-BIM问题自动解决方案的技术和商业可行性。Scan-to-BIM是指对物理结构(以密集点云的形式)进行3D扫描，并将原始空间数据转换为面向对象的、语义丰富的模型。尽管有一些技术旨在促进这一过程，但3D建模组件仍然主要是一项手动且耗时的任务。当使用所提议的技术时，如果被证明是可行的，非技术工人会对目标结构进行录像。视频被自动发送到服务器进行处理。一个独特的视频测量框架重建了结构的3D几何图形。这将生成密集的点云、边云和线云(它们仍然是原始的，但更有意义的空间数据)。然后，它以观测的形式从关键帧和空间数据中提取对象假设。然后，对联合概率分布函数进行优化，推断出三维布局。其结果是具有嵌入的几何属性和属性集的结构的面向对象的3D表示。这推动了强健智能方面的最先进技术，特别是对复杂的非结构化数据的解释。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to transform commercial construction through the democratization of scanning and automation of Building Information Modeling (BIM). Constant design and change management is a unique challenge that is costing the US construction industry billions of dollars annually. BIM allows significant reduction of these costs by facilitating an early analysis and decision-making process. The existing manual as-built BIM modeling technologies are only viable for large-scale commercial construction projects because the process is too laborious and expensive; in small projects, the projected savings hardly justify adopting the process. The proposed Scan-to-BIM technology has the potential to eliminate these barriers. Its ease-of-use, reduced file size, and automated object detection enable more scans and create more robust data models, unlocking the latent potential of the BIM process. Enormous value could be generated due to streamlining and data management capabilities that are offered by the technology in the form of accelerated project schedules, reduced number of requests for information and change orders, and timely identified design clashes. This paves the way to increasing the competitiveness of the US construction industry, by enabling new services that support automatic BIM modeling and effective infrastructure management.This Small Business Innovation Research (SBIR) Phase I project will investigate the technical and commercial feasibility of an automatic solution for the Scan-to-BIM problem in the construction industry. Scan-to-BIM refers to 3D scanning of a physical structure (in the form of a dense point cloud) and converting the raw spatial data into an object-oriented, semantically-rich model. Although there are a few technologies that aim to facilitate this process, the 3D modeling component remains primarily a manual and time-consuming task. When using the proposed technology, if proved to be feasible, a non-technical worker videotapes the target structure. The video is automatically sent to a server for processing. A unique videogrammetric framework reconstructs the 3D geometry of the structure. This generates a dense point cloud, an edge cloud, and a line cloud (which are still raw but more meaningful spatial data). It then extracts object hypotheses from key frames and spatial data in the form of observations. Afterwards, it optimizes a joint probability distribution function and infers a 3D layout. The outcome is an object-oriented 3D representation of the structure with embedded geometrical attributes and property sets. This advances the state-of-the-art in robust intelligence, particularly the interpretation of complex, unstructured data.