誰でもできる半自動3D物体キーポイント注釈と検出
Semi-automatic 3D Object Keypoint Annotation and Detection for the Masses
ロボットアームの手首カメラを使い、データ収集から注釈・学習・評価までを数時間で行える半自動3D物体キーポイント検出ツールキットを提案した。
著者: Kenneth Blomqvist, Jen Jen Chung, Lionel Ott, Roland Siegwart
分類: cs.CV, cs.RO
原文アブストラクト
Creating computer vision datasets requires careful planning and lots of time and effort. In robotics research, we often have to use standardized objects, such as the YCB object set, for tasks such as object tracking, pose estimation, grasping and manipulation, as there are datasets and pre-learned methods available for these objects. This limits the impact of our research since learning-based computer vision methods can only be used in scenarios that are supported by existing datasets. In this work, we present a full object keypoint tracking toolkit, encompassing the entire process from data collection, labeling, model learning and evaluation. We present a semi-automatic way of collecting and labeling datasets using a wrist mounted camera on a standard robotic arm. Using our toolkit and method, we are able to obtain a working 3D object keypoint detector and go through the whole process of data collection, annotation and learning in just a couple hours of active time.
