基于卡尔曼滤波的跟踪与识别集成系统

A. Vijay, Anoop K. Johnson
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引用次数: 3

摘要

从视频场景中跟踪任何对象不仅对安全应用,而且对流量分析变得更加重要。该系统通过在线数据模型和离线数据模型将低级图像处理和高级图像处理相结合,提高了系统的效率和鲁棒性。这也使得系统可以处理遮挡条件和突然的颜色强度变化条件。该系统采用中值滤波和斑点提取技术对运动目标进行检测。离线模型采用高级图像处理对运动物体进行识别。在这里,卡尔曼滤波用于复杂情况下的有效跟踪。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An integrated system for tracking and recognition using Kalman filter
Tracking of any object from a video scene becomes more critical not only for security applications but also for analyzing traffic. This system integrates low level image processing as well as high level image processing through online data model and offline data model for more efficiency and robustness. Also this makes the system to handle occlusion conditions and abrupt color intensity variation conditions. This system uses median filtering and blob extraction for moving object detection. The offline model employs high level image processing recognize the moving objects. Here the Kalman filter is used for effective tracking under complex situations.
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