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Automatic Method for Building Indoor Boundary Models from Dense Point Clouds Collected by Laser Scanners
School of Computer Engineering, Universidad Nacional de Educación a Distancia (UNED), C/Juan del Rosal, 16, 28040 Madrid, Spain
3D Visual Computing and Robotics Lab, Universidad de Castilla-La Mancha (UCLM), Paseo de la Universidad, 4, 13071 Ciudad Real, Spain
* Author to whom correspondence should be addressed.
Received: 31 August 2012; in revised form: 30 October 2012 / Accepted: 8 November 2012 / Published: 22 November 2012
Abstract: In this paper we present a method that automatically yields Boundary Representation Models (B-rep) for indoors after processing dense point clouds collected by laser scanners from key locations through an existing facility. Our objective is particularly focused on providing single models which contain the shape, location and relationship of primitive structural elements of inhabited scenarios such as walls, ceilings and floors. We propose a discretization of the space in order to accurately segment the 3D data and generate complete B-rep models of indoors in which faces, edges and vertices are coherently connected. The approach has been tested in real scenarios with data coming from laser scanners yielding promising results. We have deeply evaluated the results by analyzing how reliably these elements can be detected and how accurately they are modeled.
Keywords: 3D modeling; B-rep models; laser scanners; 3D data processing
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Cite This Article
MDPI and ACS Style
Valero, E.; Adán, A.; Cerrada, C. Automatic Method for Building Indoor Boundary Models from Dense Point Clouds Collected by Laser Scanners. Sensors 2012, 12, 16099-16115.
Valero E, Adán A, Cerrada C. Automatic Method for Building Indoor Boundary Models from Dense Point Clouds Collected by Laser Scanners. Sensors. 2012; 12(12):16099-16115.
Valero, Enrique; Adán, Antonio; Cerrada, Carlos. 2012. "Automatic Method for Building Indoor Boundary Models from Dense Point Clouds Collected by Laser Scanners." Sensors 12, no. 12: 16099-16115.