HA-ViD: A Human Assembly Video Dataset for Comprehensive Assembly Knowledge Understanding

• URL: http://arxiv.org/abs/2307.05721v1
• Date: Sun, 9 Jul 2023 08:44:46 GMT
• Title: HA-ViD: A Human Assembly Video Dataset for Comprehensive Assembly Knowledge Understanding
• Authors: Hao Zheng, Regina Lee, Yuqian Lu
• Abstract summary: HA-ViD is the first human assembly video dataset that features representative industrial assembly scenarios. We provide 3222 multi-view, multi-modality videos (each video contains one assembly task), 1.5M frames, 96K temporal labels and 2M spatial labels. We benchmark four foundational video understanding tasks: action recognition, action segmentation, object detection and multi-object tracking.
• Score: 5.233797258148846
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Understanding comprehensive assembly knowledge from videos is critical for futuristic ultra-intelligent industry. To enable technological breakthrough, we present HA-ViD - the first human assembly video dataset that features representative industrial assembly scenarios, natural procedural knowledge acquisition process, and consistent human-robot shared annotations. Specifically, HA-ViD captures diverse collaboration patterns of real-world assembly, natural human behaviors and learning progression during assembly, and granulate action annotations to subject, action verb, manipulated object, target object, and tool. We provide 3222 multi-view, multi-modality videos (each video contains one assembly task), 1.5M frames, 96K temporal labels and 2M spatial labels. We benchmark four foundational video understanding tasks: action recognition, action segmentation, object detection and multi-object tracking. Importantly, we analyze their performance for comprehending knowledge in assembly progress, process efficiency, task collaboration, skill parameters and human intention. Details of HA-ViD is available at: https://iai-hrc.github.io/ha-vid.

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