摘要
针对乒乓球机器人视觉系统中的实时跟踪问题,分别在高速和低速2种摄影条件下设计完全不同的算法对乒乓球进行跟踪识别研究。在高速摄影条件下主要利用乒乓球的5大特征信息(圆度、周长、面积、X距和Y距)设置阈值进行识别;在低速摄影条件下将机器学习和图像匹配的方法进行代入,实现对带拖影乒乓球的识别。采用基于注意力的图像分割算法对图片进行预处理,可有效解决因环境干扰等造成的像素失真问题。提出规划感兴趣区(ROI)的算法,利用乒乓球的运动特征提前确定下一帧图像中乒乓球的可能位置,从而降低计算量,缩短计算时间,实现跟踪的实时性。
The problems of real-time tracking of table tennis in the visual system of table tennis robot are focused on.Two completely different algorithms are designed to track the table tennis under two different photography conditions of high-speed and low-speed. Under high-speed photography,the five kinds of major characteristic information of table tennis are mainly used to set the threshold for identification which include roundness,circumference,area,X-distance and Y-distance. In the low-speed photography,the machine learning and matching methods are used to achieve a smearing table tennis recognition. A kind of attention-based image segmentation algorithm is used to pre-process the image,which can effectively solve the problem of pixel distortion due to environmental interference and other factors.The algorithm of planning region of interest(ROI)area is proposed. The possible position of table tennis in the next frame image is determined in advance by the movement characteristics of table tennis,which can be used to reduce the calculation amount,shorten the calculation time,and achieve the real-time tracking.
作者
季云峰
任杰
施之皓
JI Yunfeng;REN Jie;SHI Zhihao(Institute of Machine Intelligence,University of Shanghai for Science and Technology,Shanghai 200093,China;China Table Tennis College,Shanghai University of Sport,Shanghai 200438,China)
出处
《上海体育学院学报》
CSSCI
北大核心
2020年第6期70-75,共6页
Journal of Shanghai University of Sport
基金
上海市浦江人才计划项目(2019PJC073)
上海市人工智能创新发展专项支持项目。
关键词
乒乓球机器人
视觉系统
实时跟踪
注意力
图像分割
机器学习
table tennis robot
visual system
real-time tracking
attention
image segmentation
machine learning
