基于区域和颜色信息分步应用的活动目标跟踪

Joonhyun Jeong, Kyu-Won Lee
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引用次数: 0

摘要

提出了一种基于逐级应用实时图像序列的区域和颜色信息的平移和倾斜相机主动目标跟踪算法。为了降低输入序列中的环境噪声,首先进行高斯滤波。采用自适应高斯混合模型将图像分割为背景和目标。一旦检测到目标物体,在靠近目标区域的地方建立一个初始搜索窗口,并从该区域提取颜色信息。我们使用CAMShift算法实时跟踪运动物体,该算法可以利用颜色信息跟踪活动相机中的物体。正确的跟踪是通过控制平移和倾斜的量来实现的,将物体的中心位置放置到视野的中间。实验结果表明,该方法比手动窗口法更有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Active Object Tracking based on stepwise application of Region and Color Information
An active object tracking algorithm using Pan and Tilt camera based in the stepwise application of region and color information from realtime image sequences is proposed. To reduce environment noises in input sequences, Gaussian filtering is performed first. An image is divided into background and objects by using the adaptive Gaussian mixture model. Once the target object is detected, an initial search window close to an object region is set up and color information is extracted from the region. We track moving objects in realtime by using the CAMShift algorithm which enables to trace objects in active camera with the color information. The proper tracking is accomplished by controlling the amount of pan and tilt to be placed the center position of object into the middle of field of view. The experimental results show that the proposed method is more effective than the hand-operated window method.
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