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计算机系统应用英文版:2019,28(8):235-240
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基于BP回归神经网络的人体角度拟合研究
(北方工业大学 计算机学院, 北京 100144)
Human Angle Fitting Based on BP Neural Network
(College of Computer, North China University of Technology, Beijing 100144, China)
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Received:December 16, 2018    Revised:January 08, 2019
中文摘要: 基于深度学习和深度摄像机的人体动作识别方法,受其应用场景所限,均不能对视频中快变场景和静态图像中的人体动作进行识别.本文中定义了人体肢体角度空间,使用基于深度学习的人体骨骼识别框架的骨骼数据,构建8个4层BP回归神经网络.对人体的骨骼数据提取和预处理后,再对训练数据进行增维处理,通过回归神经网络进行拟合,实验和测试结果表明,该方法可以有效的对人体角度进行回归,为快变场景和静态图像中的人的动作识别提供可靠依据.
Abstract:The human motion recognition method based on depth learning and depth camera is limited by its application scene, and it cannot recognize the human motion in fast changing scene and static image. This article defines human related angle space, and builds eight four layer BP regression neural network using the human body skeleton recognition based on deep learning framework of data. After data extraction and pretreatment of the bone data of human body, training data is processed to increase the dimension, and then it is fitted through the regression neural network. The experimental results show that the proposed method can effectively regress the human body angle, provide reliable basis for human motion recognition in fast changing scene and static image.
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王景中,胡凯.基于BP回归神经网络的人体角度拟合研究.计算机系统应用,2019,28(8):235-240
WANG Jing-Zhong,HU Kai.Human Angle Fitting Based on BP Neural Network.COMPUTER SYSTEMS APPLICATIONS,2019,28(8):235-240