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

Autor:	Francisco Troncoso-Pastoriza, Javier López-Gómez, Lara Febrero-Garrido
Jazyk:	angličtina
Rok vydání:	2018
Předmět:	building lighting lamp detection pose estimation building information modelling Chemical technology TP1-1185
Zdroj:	Sensors, Vol 18, Iss 7, p 2364 (2018)
Druh dokumentu:	article
ISSN:	1424-8220 18072364
DOI:	10.3390/s18072364
Popis:	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.
Databáze:	Directory of Open Access Journals
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