【作者】 王晶晶；

【导师】 全书海；

【作者基本信息】 武汉理工大学 ， 控制科学与工程， 2010， 硕士

【摘要】 随着径赛比赛中运动员竞技水平的不断提高,径赛终点拍摄系统已成为大中型比赛中必不可少的计时设备,该设备的使用为在比赛中得出公平公正的比赛成绩提供了依据和保障。现有径赛终点拍摄系统的比赛成绩是通过终点裁判员在终点冲线图上进行判断,通过手动操作获取的。这就使比赛成绩中引入了人工干预,影响了比赛的公平性；此外,人工成绩判读需要耗费一定的时间,降低了比赛成绩获取的实时性。针对以上问题,本文开展了径赛终点冲线图中人体过终点线识别算法的研究。主要研究内容如下：首先阐述了现有径赛终点拍摄系统计时工作的基本原理,分析了线阵CCD摄像头的成像机理以及终点冲线图的特点。根据终点冲线图的特点提出了基于行中值的目标检测方法,并与其他几种目标检测方法进行对比。在目标检测的基础上,利用连通域去除背景波动引入的噪声并实现目标提取。进而对每个提取目标进行头部图像定位,根据所定位的头部图像数目确定所提取的目标中有无人体重叠或粘连情况发生。对发生重叠或粘连的人体图像,根据头部图像定位结果,提取每个人体图像躯干骨架所在的特征位置。提出了两种依据特征位置进行目标图像分离的方法,欧式距离分离法用于解决重叠较轻或轻度粘连的情况,Floyd分离法用于解决存在交叉重叠的情况。针对每个独立的人体目标图像轮廓进行分析,与距离变换轮廓分析法相比,采用泊松方程分析法能够得到躯干主体部分的轮廓。在泊松方程分析结果的基础上,提出了一种能够获取轮廓曲线上特征点的特征提取函数,定位特征点后,即可依据特征点位置提取出无损的躯干图像。进而得出冲线位置和比赛成绩。利用本文提出的基于径赛图像的人体过终点线识别算法,能够在人体目标无重叠或重叠粘连较轻的情况下得出较为准确的比赛成绩。更多还原

【Abstract】 With the continuous improvement of athletes’competitive level in track race, track end-point timer system has become an essential device in major sporting events and it guarantees exact scores and fair plays.In most existing track end-point timer system, time spent by an athlete is acquired by the operation of umpires on pictures filmed at the finishing line manually. In this way unjust factors may be generated from the inaccurate judgment of umpires, besides, at a time when the game is proceeding rather rapidly, time costed by manual manipulation is indispensable. To solve these problems, this thesis made a research on recogniton algorithm of human body over the finish line. Main contents are as the following:First, timing principles of existing track end-point timer system is introduced and imaging mechanism of linear CCD used in the system is explained.To realize human object detection,an analyse is made concerning about the features of track images,based on which a method called object detection based on line median is proposed and compared with two other object detection methods.By connected components abstraction, background noise is removed and human object is extracted. Then the head image of each extracted target is located. According to the number of human head image, determine whether overlap or adhesion occurs in target images.In the case of overlap or adhesion, trunk skeleton of each human is extracted according to head positions. Two separation methods are proposed. Euclidean distance separation method is for light overlapping or adhesions. Floyd separation method is for crossing overlapping situation.Silhouette of each single human target is analyzed.Comparing with Distance Transform method, Poisson Equation method can acquire the main contour of human trunk.Based on Poisson Equation method, a feature extraction function is proposed, which can extract non-destructive and accurate trunk image.Based on this, the accurate competition results can be obtained.In the situation of no or light overlapping and adhesion, recogniton algorithm of human body over the finish line based on track image proposed in this paper can arrive at a accurate result.更多还原