摘要
利用LUV色彩空间的特性,提出将RGB色彩空间的目标特征描述转换到LUV色彩空间,从而解决目标表面特征变化造成的目标丢失现象,提高目标跟踪算法的鲁棒性。结合卡尔曼滤波和均值漂移跟踪算法的优点,通过一种判别机制将这两个算法得到的跟踪结果进行融合,提高目标跟踪算法的准确性。通过实验证明了新方法的有效性和准确性。
A new object tracking algorithm is presented in this paper.It fused the Kalman filter and mean-shift tracking methods to utilize their merits to track object.Before that,the object feature description should be shifted to LUV from RGB.Then the object feature would be robust in color changing of video.The experiment indicated that the new algorithm is validity and veracity.
出处
《计算机工程与应用》
CSCD
北大核心
2008年第3期8-9,19,共3页
Computer Engineering and Applications
基金
国家自然科学基金(the National Natural Science Foundation of China under Grant No.60634030)
高等学校博士学科点专项科研基金(the Research Fund for the Doctoral Program of Higher Education under Grant No.20060699032)
