计算机科学 ›› 2022, Vol. 49 ›› Issue (6): 269-275.doi: 10.11896/jsjkx.210500070
赵小虎, 叶圣, 李晓
ZHAO Xiao-hu, YE Sheng, LI Xiao
摘要： 针对行为监测在现实场景下实测效果较差的情况,提出了一种新型的提取人体运动特征的方法,该方法不仅考虑了骨骼点信息,也融合了图像的环境属性信息。考虑到现有的大量实验都是在提取人体骨骼特征的基础上融合多种复杂算法进行实验分类,并未考虑到仅仅使用提取骨骼特征进行算法评估的不合理性。因此提出了一种基于骨骼特征的图像信息重建方法,并结合骨骼特征的图卷积网络和注意力机制等算法以及图像识别方法以达到人体行为识别的目的。首先使用Openpose提取骨骼点信息;然后使用图卷积和注意力进行一次分类,在一次分类的基础上通过加入骨骼点扩张系数来分割图形,从而达到对分割的图形进行分类二次精确分类的目的;最后在HMDB51数据集上进行评估,结果表明所提方法的准确度相比对比方法平均提高了5.6%,在实际测试中其有较强的优势。这表明所提方法不仅更精确,同时也更具有实际应用价值。
中图分类号:
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