A NOVEL FAST MOVING OBJECT CONTOUR TRACKING ALGORITHM

• Published in: Journal of electronics (China) Vol. 26; no. 1; pp. 94 - 100
• Main Authors: An, Guocheng, Yang, Hao, Wu, Zhenyang
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 2009; School of Information Science and Engineering, Southeast University, Nanjing 210096, China
• Subjects: Electrical Engineering; Engineering; 平均值转换; 目标轮廓跟踪; 粒子滤波器; Kernel scale; Mean shift; TP391.41; Particle filter; Object contour tracking
• ISSN: 0217-9822; 1993-0615
• DOI: 10.1007/s11767-007-0159-0

If a somewhat fast moving object exists in a complicated tracking environment, snake＇s nodes may fall into the inaccurate local minima. We propose a mean shift snake algorithm to solve this problem. However, if the object goes beyond the limits of mean shift snake module operation in successive sequences, mean shift snake＇s nodes may also fall into the local minima in their moving to the new object position. This paper presents a motion compensation strategy by using particle filter; therefore a new Particle Filter Mean Shift Snake （PFMSS） algorithm is proposed which combines particle filter with mean shift snake to fulfill the estimation of the fast moving object contour. Firstly, the fast moving object is tracked by particle filter to create a coarse position which is used to initialize the mean shift algorithm. Secondly, the whole relevant motion information is used to compensate the snake＇s node positions. Finally, snake algorithm is used to extract the exact object contour and the useful information of the object is fed back. Some real world sequences are tested and the results show that the novel tracking method have a good performance with high accuracy in solving the fast moving problems in cluttered background.