ASCE International Conference on Computing in Civil Engineering 2019
Worksite Object Characterization for Automatically Updating Building Information Models
Publication: Computing in Civil Engineering 2019: Visualization, Information Modeling, and Simulation
ABSTRACT
Automated data capture systems could significantly improve the efficiency and productivity of the architecture, engineering, construction, and facility management (AEC/FM) industry. However, automatically collecting spatiotemporal information in an unstructured environment such as a construction site or a work place remains a time consuming and challenging task. This paper presents a new approach to automated data capture and processing, referred to as object characterization. In object characterization, the goal is to identify common objects in a scene and extract rich semantic information about those objects. A novel 2D-3D object detection algorithm is designed for detection and characterization of common worksite objects. The proposed system has applications in automated surveying and data collection, especially in applications which leverage unmanned aerial vehicles or mobile robots. To demonstrate this utility, the proposed system is deployed on a mobile robot and used to detect newly placed objects in a worksite environment.
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Acknowledgement
This research is partially supported by the Center for Integrated Facility Engineering at Stanford University. The first author is also supported by the John A. Blume fellowship.
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Published In
Computing in Civil Engineering 2019: Visualization, Information Modeling, and Simulation
Pages: 303 - 311
Editors: Yong K. Cho, Ph.D., Georgia Institute of Technology, Fernanda Leite, Ph.D., University of Texas at Austin, Amir Behzadan, Ph.D., Texas A&M University, and Chao Wang, Ph.D., Louisiana State University
ISBN (Online): 978-0-7844-8242-1
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© 2019 American Society of Civil Engineers.
History
Published online: Jun 13, 2019
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