2024 03 v.39;No.167 210-232
基于图卷积网络的人体骨架行为识别方法综述
基金项目(Foundation):
国家自然科学基金资助项目(61976127)
邮箱(Email):
DOI:
中文作者单位:
山东师范大学信息科学与工程学院;
摘要(Abstract):
基于骨架数据的人体行为识别已成为计算机视觉领域最热门和最重要的研究课题之一。相较于其他数据类型，人体骨架数据不受光照、背景、视角变化的影响，使得该类行为识别方法具有更强的鲁棒性。此外，骨架数据是以拓扑图结构的形式存在，而图卷积是一种基于图结构的深度学习方法，能够高效地对人体骨架数据的特征进行提取和分类。因此，基于图卷积的方法已经成为处理骨架数据的主流。针对基于图卷积的行为识别方法的前沿性，对其进行全面和系统的总结和分析具有十分重要的意义。本文主要对基于图卷积方法行为识别技术的最新进展进行全面的综述，对相关方法进行分类与总结，并对基准数据集进行详细研究，最后讨论了未来的研究方向和趋势。
关键词(KeyWords):
骨架数据;;图卷积网络;;行为识别
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基本信息:
DOI：
中图分类号:TP391.41;TP183
引用信息:
[1]吕蕾,庞辰.基于图卷积网络的人体骨架行为识别方法综述[J].山东师范大学学报(自然科学版),2024,39(03):210-232.
基金信息:
国家自然科学基金资助项目(61976127)
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