2台のカメラを用いた3D物体位置推定のための実世界データセットの自動構築
Automatic Construction of Real-World Datasets for 3D Object Localization using Two Cameras
産業用ロボットの幾何情報を利用して2台のカメラ画像と物体の3D位置を自動同期し、ステレオ画像による物体位置推定用の大規模データセットを自動生成する手法を提案した。
著者: Joris Guérin, Olivier Gibaru, Eric Nyiri, Stéphane Thiery
分類: cs.CV, cs.RO
原文アブストラクト
Unlike classification, position labels cannot be assigned manually by humans. For this reason, generating supervision for precise object localization is a hard task. This paper details a method to create large datasets for 3D object localization, with real world images, using an industrial robot to generate position labels. By knowledge of the geometry of the robot, we are able to automatically synchronize the images of the two cameras and the object 3D position. We applied it to generate a screw-driver localization dataset with stereo images, using a KUKA LBR iiwa robot. This dataset could then be used to train a CNN regressor to learn end-to-end stereo object localization from a set of two standard uncalibrated cameras.
