上海大学学报(自然科学版) ›› 2022, Vol. 28 ›› Issue (2): 179-200.doi: 10.12066/j.issn.1007-2861.2316
• 特邀综述 • 下一篇
收稿日期:
2021-03-26
出版日期:
2022-04-30
发布日期:
2022-04-28
通讯作者:
彭亚新
E-mail:yaxin.peng@shu.edu.cn
作者简介:
彭亚新(1979--), 女, 教授, 博士生导师, 博士,研究方向为数学图像分析、数据挖掘等.E-mail: yaxin.peng@shu.edu.cn基金资助:
Received:
2021-03-26
Online:
2022-04-30
Published:
2022-04-28
Contact:
PENG Yaxin
E-mail:yaxin.peng@shu.edu.cn
摘要:
骨架数据是通过对动作的空间几何位置进行编码获取,可以避免冗余背景信息的干扰, 是动作识别领域常用的数据类型之一.现有骨架数据的动作识别主要分为经典的骨架数据表征和基于深度学习的骨架动作识别应用.相较于传统欧氏度量下的识别方法,流形为更好地研究非线性结构提供了重要数学工具. 然而,目前仍缺乏利用流形假设对骨架数据进行动作识别的相关总结. 因此,从骨架表示、轨迹时间对齐、动作序列表征以及动作分类 4 个关键步骤出发,系统地总结了基于流形假设的动作识别工作,对比了各项工作在基准数据集上的表现. 最后,根据当前动作识别工作的发展趋势,对流形假设在动作识别方向上的进一步改进进行了展望.
中图分类号:
彭亚新, 赵倩. 基于流形假设的骨架序列动作识别算法[J]. 上海大学学报(自然科学版), 2022, 28(2): 179-200.
PENG Yaxin, ZHAO Qian. Skeleton-based action recognition by manifold assumption[J]. Journal of Shanghai University(Natural Science Edition), 2022, 28(2): 179-200.
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