TY - JOUR A2 - Wang, Wei AU - Fu, Qiang AU - Zhang, xin桂AU - Xu, Jinxiu AU - Zhang，Haimin PY - 2020 DA - 2020/11/21 TI -捕捉虚拟现实的三维人体运动姿势基于视频识别的SP - 8857748六世- 2020 AB -运动姿态捕获技术可以有效地解决困难的问题定义角色运动的过程中,3 d动画生产和角色运动大大减少工作量控制，从而提高动画开发的效率和人物运动的逼真度。运动姿态捕捉技术广泛应用于虚拟现实系统、虚拟训练场地以及对一般物体运动轨迹的实时跟踪。提出了一种适合于嵌入式的姿态估计算法。之前的集中卡尔曼滤波分为两步卡尔曼滤波。根据传感器的不同特性，分别对其进行处理，以隔离传感器之间的交叉影响。提出了一种基于模糊逻辑的自适应调整方法。利用环境的加速度、角速度和地磁场强度作为模糊逻辑的输入，判断载体的运动状态，然后调整滤波器的协方差矩阵。将传感器的自适应调整转化为对运动状态的识别。 For the study of human motion posture capture, this paper designs a verification experiment based on the existing robotic arm in the laboratory. The experiment shows that the studied motion posture capture method has better performance. The human body motion gesture is designed for capturing experiments, and the capture results show that the obtained pose angle information can better restore the human body motion. A visual model of human motion posture capture was established, and after comparing and analyzing with the real situation, it was found that the simulation approach reproduced the motion process of human motion well. For the research of human motion recognition, this paper designs a two-classification model and human daily behaviors for experiments. Experiments show that the accuracy of the two-category human motion gesture capture and recognition has achieved good results. The experimental effect of SVC on the recognition of two classifications is excellent. In the case of using all optimization algorithms, the accuracy rate is higher than 90%, and the final recognition accuracy rate is also higher than 90%. In terms of recognition time, the time required for human motion gesture capture and recognition is less than 2 s. SN - 1076-2787 UR - https://doi.org/10.1155/2020/8857748 DO - 10.1155/2020/8857748 JF - Complexity PB - Hindawi KW - ER -