激光与光电子学进展, 2020, 57 (24): 241003, 网络出版: 2020-12-02   

结合稠密轨迹与视频显著性特征的人体动作识别 下载: 1003次

Human-Body Action Recognition Based on Dense Trajectories and Video Saliency
作者单位
1 兰州交通大学电子与信息工程学院, 甘肃 兰州 730070
2 甘肃省人工智能与图形图像工程研究中心, 甘肃 兰州 730070
3 甘肃省轨道交通装备系统动力学与可靠性重点实验室, 甘肃 兰州 730070
引用该论文

高德勇, 康自兵, 王松, 王阳萍. 结合稠密轨迹与视频显著性特征的人体动作识别[J]. 激光与光电子学进展, 2020, 57(24): 241003.

Deyong Gao, Zibing Kang, Song Wang, Yangping Wang. Human-Body Action Recognition Based on Dense Trajectories and Video Saliency[J]. Laser & Optoelectronics Progress, 2020, 57(24): 241003.

参考文献

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高德勇, 康自兵, 王松, 王阳萍. 结合稠密轨迹与视频显著性特征的人体动作识别[J]. 激光与光电子学进展, 2020, 57(24): 241003. Deyong Gao, Zibing Kang, Song Wang, Yangping Wang. Human-Body Action Recognition Based on Dense Trajectories and Video Saliency[J]. Laser & Optoelectronics Progress, 2020, 57(24): 241003.

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