期刊论文

Human action recognition based on fusion features

中文

计算机工程与设计

1000-7024

2019

40

5

1394-1400

10.16208/j.issn1000-7024.2019.05.036

(2015BAK33B02):“十二五”科技支撑计划基金项目 (CCNU18TS041、CCNU18QN020):华中师范大学自主科研基金项目

本校为第一机构

针对复杂的人体动作识别率较低以及单一特征的不足的问题,提出基于Haar小波变换的改进轮廓特征以及多种特征融合的动作识别方法.在第一组实验中对小波变换后的单轮廓特征采用动态时间规整(DTW)算法进行动作序列匹配;第二组实验中提取每帧深度图像的时空兴趣点并进行匹配,在轮廓特征基础上融合加速稳健特征(SURF)和光流直方图(HOF)运动特征作为局部特征;第三组实验在第二组实验的基础上加入骨骼特征.后两组实验均采用线性支持向量机(SVM)对提取的特征进行训练和分类,并在公开数据集MSR Action3D上进行验证.实验结果验证了改进后轮廓特征的有效性,两组融合特征的动作识别方法在同类算法中具有较高...

Aiming at the problem of low recognition rate and the lacks of single feature of complex human actions,an improved contour feature based on Haar wavelet transform and action recognition method with multiple feature fusion were proposed.In the first group of experiments,dynamic time warping (DTW) algorithm was utilized to match template for motion sequences of the single contour features after wavelet transform.In the second experiment,the spatio-temporal interest points of each depth image were extracted and matched,and the speeded up robust features (SURF) and the histograms of oriented optic...