摘要
人体动作的复杂性、类内差异和视角变化等因素对准确识别人体动作造成一定影响。基于深度相机能同时记录深度图像和实时提取骨骼信息的优势,提出一种基于深度图像和骨骼信息的动作识别方法。使用深度图像序列生成运动历史点云并提取全局特征,同时从三维骨骼信息中提取局部动作特征,对得到的点云特征和骨骼特征进行特征融合,构建出一种多模特征融合的动作识别方法。在MSR-Action3D和UTKinectAction3D两个数据集进行验证,均达到了95%以上的识别率,证明了该方法的有效性。
The complexity of human body movements,within-class differences and perspective changes hinder the accurate recognition of human movements.Depth camera can simultaneously record depth images and extract skeleton information,based on that,a motion recognition method is proposed.Depth image sequence is used to generate a motion history point cloud and extract global features and local motion features from 3D skeleton information.Point cloud features and skeleton features are fused to construct a multi-modal feature fusion action recognition method.Tests on two data sets of MSR-Action3D and UTKinect-Action3D show that recognition rates are above95%,which proves the effectiveness of the method.
作者
张良
钱毅敏
ZHANG Liang;QIAN Yimin(College of Electronics and Automation,CAUC,Tianjin 300300,China)
出处
《中国民航大学学报》
CAS
2021年第2期54-60,共7页
Journal of Civil Aviation University of China
基金
国家自然科学基金项目(61179045)。
关键词
动作识别
深度图像
骨骼信息
特征融合
action recognition
depth maps
skeleton information
feature fusion
