| 基于改进深度学习方法的人体动作识别综述 |
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| 引用本文： | 朱相华,智敏.基于改进深度学习方法的人体动作识别综述[J].计算机应用研究,2022,39(2):342-348. |
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| 作者姓名： | 朱相华 智敏 |
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| 作者单位： | 内蒙古师范大学计算机科学技术学院 |
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| 基金项目： | 内蒙古自治区高等学校科学研究资助项目(NJZZ21004);内蒙古自然科学基金资助项目(2018MS06008)。 |
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| 摘 要： | 为了梳理深度学习方法在人体动作识别领域的发展脉络，对该领域近年来最具代表性的模型和算法进行了综述。以人体动作识别任务流程为线索，详细阐述了深度学习方法在视频预处理阶段、网络结构上的最新成果及其优缺点。介绍了人体动作识别相关的两类数据集，并选取常用的几种进行具体说明。最后，对人体动作识别未来的研究方向进行了探讨与展望。
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| 关 键 词： | 人体动作识别 深度学习 视频预处理 网络结构 数据集 |
| 收稿时间： | 2021/7/27 0:00:00 |
| 修稿时间： | 2022/1/14 0:00:00 |
Review of human action recognition based on improved deep learning methods |
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| Zhu Xianghua and Zhi Min.Review of human action recognition based on improved deep learning methods[J].Application Research of Computers,2022,39(2):342-348. |
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| Authors: | Zhu Xianghua and Zhi Min |
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| Affiliation: | (College of Computer Science&Technology,Inner Mongolia Normal University,Hohhot 010022,China) |
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| Abstract: | In order to sort out the development of deep learning methods in the field of human action recognition, this paper summarized the most representative models and algorithms in this field in recent years. Firstly, it described in detail the latest achievements, advantages and disadvantages and network structure of deep learning methods in video pre-processing stage based on the task flow of human action recognition. Then, it introduced two kinds of datasets related to human action recognition. Finally, it discussed and prospected the future research direction of human action recognition. |
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| Keywords: | human action recognition deep learning video pre-processing network structure datasets |
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