摘要
为了提高Camshift跟踪方法在复杂环境下的跟踪性能,应用被跟踪目标内部各特征像素间的交比不变原理,提出了一种改进的Camshift跟踪方法。该方法通过分析被跟踪的目标模型,计算出其内部各特征像素间的坐标关系;将内部数据间的交比不变量作为所提出的跟踪方法的约束条件,对跟踪错误的像素点进行校正,并将跟踪过程中连续两帧图像的内部特征像素间的距离比作为跟踪效果的评判标准。用改进的Camshift跟踪方法分别对标准测试视频内的视频信息和实际拍摄的视频信息进行了测试。结果显示,该方法在两种复杂环境实验条件下,跟踪目标的距离偏差都能保持在15pixel以内,对单帧图像平均处理时间在20ms以内。试验结果表明,该方法对复杂环境下的目标具有良好的跟踪效果,跟踪性能稳定,跟踪效率高,可以满足跟踪系统实时性的要求。
To optimize the tracking property of Camshift tracking method under a complex environment,the principle of constant cross ratio of internal feature pixels in tracked objects was used to improve the Camshift tracking method.By analyzing the tracked object model,the coordinate relationship among the internal feature pixels was calculated by using this method,then the internal datum＇s cross ratio invariant was regarded as the constraint condition of the proposed tracking method to correct the wrong tacking pixel points,and the distance ratio of internal feature pixels between two successive frames in the tracking process was taken as the judgment criteria.This proposed Camshift tracking method was used to test the video information respectively in a standard test video and in an actually shot video.Comparison results show that the distance deviation of the tracked object maintains within 15 pixel and the average handling time of single pixel is within 20 ms under the condition of two kinds of complex environment experiments.It concludes that the improved method has stable tracking property,higher tracking efficiency and good tracking results under the complex environment,and it satisfies the requirement of real-time tracking systems.
出处
《光学精密工程》
EI
CAS
CSCD
北大核心
2016年第4期945-953,共9页
Optics and Precision Engineering
基金
山西省科技攻关项目(No.20130321005-04)
作者简介
黄晋英（1971-），女，山西代县人，教授，博士生导师，2010年于北京理工大学获得博士学位，主要从事智能车辆、检测与控制等方面的研究。E-mail：yl-bhjy@qq．com
宋国浩（1990-），男，山东曲阜人，硕士研究生，2014年于中北大学获得学士学位，主要从事机械工程、机器视觉的研究。E-mail：1010057819@qq．com
