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

利用计算机视觉方法检测建筑物中的照明元件，通过引入两项改进措施提高系统精确性：首先，在建筑信息模型的几何信息基础上对检测姿态的初始估计和改进估计进行优化方法中引入方向约束，其次，在引入方向约束后通过附加的重新投影误差过滤步骤来排除错误姿态，从而在保持定位和识别误差较低的同时大大增加检测数量。通过五个不同案例研究使用超过30,000张图片进行测试，结果显示在检测数量、正确模型和状态识别的比例以及检测与参考位置之间的距离方面均有所改善。

基于计算机视觉的建筑物灯具检测的方向受限系统