Orientation-Constrained System for Lamp Detection in Buildings Based on
  Computer Vision
Francisco Troncoso-Pastoriza Pablo Eguía-Oller Rebeca P. Díaz-Redondo Enrique Granada-Álvarez Aitor Erkoreka
Computer vision is used in this work to detect lighting elements in buildings
with the goal of improving the accuracy of previous methods to provide a
precise inventory of the location and state of lamps. Using the framework
developed in our previous works, we introduce two new modifications to enhance
the system: first, a constraint on the orientation of the detected poses in the
optimization methods for both the initial and the refined estimates based on
the geometric information of the building information modelling (BIM) model;
second, an additional reprojection error filtering step to discard the
erroneous poses introduced with the orientation restrictions, keeping the
identification and localization errors low while greatly increasing the number
of detections. These~enhancements are tested in five different case studies
with more than 30,000 images, with results showing improvements in the number
of detections, the percentage of correct model and state identifications, and
the distance between detections and reference positions