基于计算机视觉技术的图像运动目标检测与跟踪算法研究

Chunsheng Chen, Ding Li
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引用次数: 13

摘要

为了改进视频图像处理技术,本文提出了一种基于计算机视觉技术的运动目标检测与跟踪算法。首先从理论和实验两方面全面比较帧间差分法和背景差分模型法的检测性能,然后选择Robert边缘检测算子对车辆进行边缘检测。研究结果表明,本文算法在跟踪运动目标时每帧运行时间最长,约为CamShift算法单帧运行时间的2.3倍。该算法运行效率高,能够满足前景目标实时跟踪的要求。该算法具有最高的跟踪精度,减少了时间消耗,并且跟踪帧偏离目标真实位置的误差最小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on the Detection and Tracking Algorithm of Moving Object in Image Based on Computer Vision Technology
In order to improve the video image processing technology, this paper presents a moving object detection and tracking algorithm based on computer vision technology. Firstly, the detection performance of the interframe difference method and the background difference model method is compared comprehensively from both theoretical and experimental aspects, and then the Robert edge detection operator is selected to carry out edge detection of the vehicle. The research results show that the algorithm proposed in this paper has the longest running time per frame when tracking a moving target, which is about 2.3 times that of the single frame running time of the CamShift algorithm. The algorithm has high running efficiency and can meet the requirements of real-time tracking of a foreground target. The algorithm has the highest tracking accuracy, the time consumption is reduced, and the error of the tracking frame deviating from the real position of the target is the least.
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