[2204.09271] A Survey of Video-based Action Quality Assessment
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Computer Science > Computer Vision and Pattern Recognition

arXiv:2204.09271 (cs)
[Submitted on 20 Apr 2022]

Title:A Survey of Video-based Action Quality Assessment

Authors:Shunli Wang, Dingkang Yang, Peng Zhai, Qing Yu, Tao Suo, Zhan Sun, Ka Li, Lihua Zhang
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Abstract:Human action recognition and analysis have great demand and important application significance in video surveillance, video retrieval, and human-computer interaction. The task of human action quality evaluation requires the intelligent system to automatically and objectively evaluate the action completed by the human. The action quality assessment model can reduce the human and material resources spent in action evaluation and reduce subjectivity. In this paper, we provide a comprehensive survey of existing papers on video-based action quality assessment. Different from human action recognition, the application scenario of action quality assessment is relatively narrow. Most of the existing work focuses on sports and medical care. We first introduce the definition and challenges of human action quality assessment. Then we present the existing datasets and evaluation metrics. In addition, we summarized the methods of sports and medical care according to the model categories and publishing institutions according to the characteristics of the two fields. At the end, combined with recent work, the promising development direction in action quality assessment is discussed.
Comments: 9 pages, 6 figures, conference paper
Subjects: Computer Vision and Pattern Recognition (cs.CV)
ACM classes: I.4.9; I.2.10
Cite as: arXiv:2204.09271 [cs.CV]
  (or arXiv:2204.09271v1 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.2204.09271
Related DOI: https://doi.org/10.1109/INSAI54028.2021.00029

Submission history

From: Shunli Wang [view email]
[v1] Wed, 20 Apr 2022 07:29:00 UTC (939 KB)
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