Automated As-Is Modeling with Visual and Spatial Data Fusion

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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.