摘要
Mean-Shift算法无法自动跟踪目标,且对目标形状要求较苛刻。针对该问题,提出一种基于形状感应的运动目标跟踪算法,采用混合高斯分布对背景建模,协助Mean-Shift算法自动定位初始目标,增加描述形状的协方差参数,使跟踪能感受到目标形状的变化。实验结果表明,该算法基本解决了自动定位问题及形状变化问题,在保证实时性的前提下,跟踪准确度提高40%以上。
A moving object tracking algorithm based on shape induction is proposed to solve problems of the Mean-Shift algorithm,which can not track the targets automatically and adapt well to the shape changes of objects.It obtains initial contour of objects automatically by building a background image with mixture Gaussian distribution.The parameter of covariance matrix is added to Mean-Shift algorithm to feel the shape changes of objects.Experimental results indicate this algorithm solves the problems concerned with automatic positioning and shape changes and the accuracy is increased by 40% at least with real-time guaranteed.
出处
《计算机工程》
CAS
CSCD
北大核心
2011年第22期143-144,共2页
Computer Engineering
基金
国家自然科学基金资助项目(60873003)
广东省教育部产学研结合基金资助项目(2009B090300302)
