Automated As-Is Modeling with Visual and Spatial Data Fusion

这项建议的目的是评估申请人提出的框架是否可以将建筑内部重建为面向对象的模型。根据拟议的框架，首先使用便携式视觉和空间传感系统测量建筑物内部，该系统提供视频帧和每像素深度值的流。视频帧中的建筑元素基于它们的视觉模式被识别。占用的像素用语义标签来标记，例如“柱”或“墙”。同时，通过匹配任意两个视频帧的联合视觉特征的位置并评估特征的深度值来提取任意两个视频帧之间的点状3D对应关系。基于这些3D对应关系，估计了帧之间的成对相对变换。这样，帧中的像素就可以对齐，形成3D点的“云”。根据先前分配给像素的标签，云中的点可以被分成多个部分并进行参数化建模。这种面向对象的参数化模型表示了感知到的建筑内部，可以用于建筑内部的构造和改造。这项研究背后的动机在于当前现有建模过程的手动和耗时的性质。原状模型记录了建筑物的现有状况，这对许多评估和管理任务很有用，例如翻新/翻新规划、维护计划、项目质量控制等。然而，目前的原状建模过程需要大量的人工编辑和更正工作，这可能占整个建模工作的三分之二以上。大量的人工工作增加了建模成本，并限制了原有模型在绝大多数建筑和改造项目中的使用。因此，由于设计和施工更改而返工的情况时有发生，成本高达合同价值的10.29%。任何旨在使这一建模过程自动化的努力都将增加原样模型在土木工程中的潜在使用，并减少不必要的返工。考虑到2010年建筑业在加拿大是一项738亿美元的业务，返工减少1%将带来7590万美元的节省。

The objective of this proposal is to evaluate whether a framework proposed by the applicant can reconstruct building interiors into an object-oriented model. According to the proposed framework, building interiors are first surveyed with a portable visual and spatial sensing system, which provides a stream of video frames along with per-pixel depth values. Building elements in the video frames are recognized based on their visual patterns. The occupying pixels are tagged with semantic labels, such as "column" or "wall". Meanwhile, a set of point-wise 3D correspondences between any two video frames are extracted by matching the locations of their joint visual features and evaluating the features' depth values. Based on these 3D correspondences, the pair-wise relative transformation between the frames is estimated. This way, the pixels in the frames can be aligned to form a "cloud" of 3D points. According to the labels previously assigned to the pixels, the points in the cloud can be divided into multiple parts and modeled parametrically. This object-oriented parametric model represents the perceived building interiors, and can be used for building interior construction and retrofit. The motivation behind this research lies in the manual and time-consuming nature of the current as-is modeling process. As-is models record building's existing conditions, which are useful for many assessment and management tasks, such as renovation/retrofit planning, maintenance scheduling, project quality control, etc. However, the current as-is modeling process requires a lot of manual editing and correction work, which could take up over two thirds of the overall modeling effort. The large volume of manual work increases modeling cost, and limits the use of as-is models in the vast majority of construction and retrofit projects. As a result, rework due to design and construction changes always happens, which costs up to 10.29% of the contract values. Any efforts towards automating this modeling process will increase the potential use of as-is models in civil projects and reduce unnecessary rework. Considering that construction was a $73.8 billion business in Canada in 2010, 1% of rework reduction would lead up to $75.9 million savings.