Study on Local Optical Flow Method Based on YOLOv3 in Human Behavior Recognition

• 作者: Hao Zheng Jianfang Liu Mengyi Liao
• 来源期刊: 电脑和通信(英文)
• 学科: 工学
• 关键词: YOLOv3 Local Optical Flow Method Human Behavior Recognition
• 年，卷（期）: dnhtxyw_2021,（1）
• 页码范围: 10-18
• 页数: 9页
• 分类号: TN9

摘要

In the process of human behavior recognition, the traditional dense optical flow method has too many pixels and too much overhead, which limits the running speed. This paper proposed a method combing YOLOv3 (You Only Look Once v3) and local optical flow method. Based on the dense optical flow method, the optical flow modulus of the area where the human target is detected is calculated to reduce the amount of computation and save the cost in terms of time. And then, a threshold value is set to complete the human behavior identification. Through design algorithm, experimental verification and other steps, the walking, running and falling state of human body in real life indoor sports video was identified. Experimental results show that this algorithm is more advantageous for jogging behavior recognition.