A Method for Robust Recognition and Tracking of Multiple Objects

摘要：

This paper presents an accurate and flexible method for robust recognition and tracking of multiple objects in video sequence. We calculate color moments and wavelet moments for each detected object. Based on the extracted moment features, the SVM achieves optimal object recognition performance. The object recognition rate is above 98.53％. Since the tracking accuracy of feature matching method could be degraded by occlusion, we add a Kalman filter tracking framework based on object recognition to improve multiple objects tracking. The previous object recognition module improves the performance and the accuracy of the Kalman filter tracking framework. Results obtained suggest that our tracking algorithm is very effective and robust even in challenging tracking conditions like occlusion and background clutter.

作者: TAN Fang GUAN Qing XU Sheng FENG Shi-min

作者单位: School of Communication and Information, University of Electronic Science and Technology of China, Cheng Du, China

会议类型: 国际会议

会议名称: 2009国际通信电路与系统学术会议(ICCCAS 2009)(2009 International Conference on Communications，Circuits and Systems)

会议地点: 成都

会议语种:英文

页码: 464-468

在线出版日期: 2009-07-23（万方平台首次上网日期，不代表论文的发表时间）