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Sensors 2018, 18(7), 2364; https://doi.org/10.3390/s18072364

Generalized Vision-Based Detection, Identification and Pose Estimation of Lamps for BIM Integration

1
School of Industrial Engineering, University of Vigo, Campus Universitario, 36310 Vigo, Spain
2
Defense University Center, Spanish Naval Academy, Plaza de España, s/n, 36920 Marín, Spain
*
Author to whom correspondence should be addressed.
Received: 22 June 2018 / Revised: 16 July 2018 / Accepted: 18 July 2018 / Published: 20 July 2018
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Abstract

This paper introduces a comprehensive approach based on computer vision for the automatic detection, identification and pose estimation of lamps in a building using the image and location data from low-cost sensors, allowing the incorporation into the building information modelling (BIM). The procedure is based on our previous work, but the algorithms are substantially improved by generalizing the detection to any light surface type, including polygonal and circular shapes, and refining the BIM integration. We validate the complete methodology with a case study at the Mining and Energy Engineering School and achieve reliable results, increasing the successful real-time processing detections while using low computational resources, leading to an accurate, cost-effective and advanced method. The suitability and the adequacy of the method are proved and concluded. View Full-Text
Keywords: building lighting; lamp detection; pose estimation; building information modelling building lighting; lamp detection; pose estimation; building information modelling
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Troncoso-Pastoriza, F.; López-Gómez, J.; Febrero-Garrido, L. Generalized Vision-Based Detection, Identification and Pose Estimation of Lamps for BIM Integration. Sensors 2018, 18, 2364.

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