スマートインフラ魚眼カメラの事前地図への位置合わせ
Localization of a Smart Infrastructure Fisheye Camera in a Prior Map for Autonomous Vehicles
魚眼カメラ画像と衛星BEV画像の特徴マッチングで初期姿勢を推定し、LiDAR反射強度との相互情報量最大化で精緻化することで、インフラカメラを事前地図に高精度に位置合わせする手法を提案した。
著者: Subodh Mishra, Armin Parchami, Enrique Corona, Punarjay Chakravarty, Ankit Vora, Devarth Parikh, Gaurav Pandey
分類: cs.RO
原文アブストラクト
This work presents a technique for localization of a smart infrastructure node, consisting of a fisheye camera, in a prior map. These cameras can detect objects that are outside the line of sight of the autonomous vehicles (AV) and send that information to AVs using V2X technology. However, in order for this information to be of any use to the AV, the detected objects should be provided in the reference frame of the prior map that the AV uses for its own navigation. Therefore, it is important to know the accurate pose of the infrastructure camera with respect to the prior map. Here we propose to solve this localization problem in two steps, \textit{(i)} we perform feature matching between perspective projection of fisheye image and bird's eye view (BEV) satellite imagery from the prior map to estimate an initial camera pose, \textit{(ii)} we refine the initialization by maximizing the Mutual Information (MI) between intensity of pixel values of fisheye image and reflectivity of 3D LiDAR points in the map data. We validate our method on simulated data and also present results with real world data.
