摘要
针对Mean Shift算法在目标跟踪过程中因核窗宽不变导致目标尺度变化时定位不精确的问题,提出了融入边缘检测的方法计算目标大小,从而实现自适应调整核窗宽的改进算法。当目标丢失和发生遮挡时,结合Kalman滤波器对下一帧中目标位置进行预测,提出改进的跟踪算法,有效提高了跟踪的准确性和鲁棒性。
For the problem of nuclear window width unchanged during the object tracking , the edge detection algorithms extract the target measure is introduced to self-adapt the Mean Shift algorithm of changing in target scale issues . When the object is lost and occlusion , the Kalman filter is used to estimate the possible position of the object in the next frame . The improved algorithm has effectively improved the accuracy and robustness of the tracking algorithm .
出处
《微型机与应用》
2013年第22期41-43,共3页
Microcomputer & Its Applications
基金
国家自然科学基金项目(61170102)
湖南省自然科学基金项目(11JJ3070)
湖南科技科技发展项目(2011GK3145)
