论文标题
联系人：带有物体接触和手姿势的grasps数据集
ContactPose: A Dataset of Grasps with Object Contact and Hand Pose
论文作者
论文摘要
抓握对于人类是自然的。但是，它涉及复杂的手部构型和软组织变形，这可能会导致手与物体之间的复杂接触区域。理解和建模这种接触可能会改善手动模型，AR/VR体验和机器人抓握。但是，我们目前缺少与其他数据模式配对的手动对象触点数据集，这对于开发和评估接触建模技术至关重要。我们介绍了ContactPose，这是第一个手动对象触点的数据集与手姿势，对象姿势和RGB-D图像配对。 ContactPose具有25个家用物体的2306个独特的盖帽，由50名参与者抓住了2个功能意图，超过2.9 m rgb-d抓握图像。接触数据的分析揭示了手姿势与接触之间的有趣关系。我们使用这些数据严格评估各种数据表示，文献启发式和接触建模的学习方法。数据，代码和训练有素的模型可在https://contactpose.cc.gatech.edu上找到。
Grasping is natural for humans. However, it involves complex hand configurations and soft tissue deformation that can result in complicated regions of contact between the hand and the object. Understanding and modeling this contact can potentially improve hand models, AR/VR experiences, and robotic grasping. Yet, we currently lack datasets of hand-object contact paired with other data modalities, which is crucial for developing and evaluating contact modeling techniques. We introduce ContactPose, the first dataset of hand-object contact paired with hand pose, object pose, and RGB-D images. ContactPose has 2306 unique grasps of 25 household objects grasped with 2 functional intents by 50 participants, and more than 2.9 M RGB-D grasp images. Analysis of ContactPose data reveals interesting relationships between hand pose and contact. We use this data to rigorously evaluate various data representations, heuristics from the literature, and learning methods for contact modeling. Data, code, and trained models are available at https://contactpose.cc.gatech.edu.
