The most popular evaluation metric for object detection in 2D images is Intersection over Union (IoU). Existing implementations of the IoU metric for 3D object detection usually neglect one or more degrees of freedom. In this paper, we first derive the analytic solution for three dimensional bounding boxes. As a second contribution, a closed-form solution of the volume-to-volume distance is derived. Finally, the Bounding Box Disparity is proposed as a combined positive continuous metric. We provide open source implementations of the three metrics as standalone python functions, as well as extensions to the Open3D library and as ROS nodes.
翻译:2D图像中天体探测最流行的评价尺度是Union(IoU)的交叉点,3D天体探测IoU指标的现有实施通常忽视一个或多个自由度。在本文中,我们首先为3维捆绑框得出分析解决方案。作为第二个贡献,还得出了量到量距离的封闭式解决方案。最后,提出了“宽箱差异”这一组合积极的连续连续指标。我们提供了3个标准作为独立光谱功能的开放源实施,以及开放3D图书馆和ROS节点的扩展。