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首页> 外文期刊>Journal of Mechatronics, Electrical Power, and Vehicular Technology >Optimized object tracking technique using Kalman filter
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Optimized object tracking technique using Kalman filter

机译:使用卡尔曼滤波器的优化目标跟踪技术

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This paper focused on the design of an optimized object tracking technique which would minimize the processing time required in the object detection process while maintaining accuracy in detecting the desired moving object in a cluttered scene. A Kalman filter based cropped image is used for the image detection process as the processing time is significantly less to detect the object when a search window is used that is smaller than the entire video frame. This technique was tested with various sizes of the window in the cropping process. MATLAB ? was used to design and test the proposed method. This paper found that using a cropped image with 2.16 multiplied by the largest dimension of the object resulted in significantly faster processing time while still providing a high success rate of detection and a detected center of the object that was reasonably close to the actual center.
机译:本文着重于优化对象跟踪技术的设计,该技术将在保持复杂场景中检测所需运动对象的准确性的同时,最大限度地减少对象检测过程中所需的处理时间。当使用的搜索窗口小于整个视频帧时,基于卡尔曼滤波器的裁剪图像将用于图像检测过程,因为处理时间大大缩短了检测对象的时间。在裁剪过程中使用各种大小的窗口对这项技术进行了测试。 MATLAB的?被用来设计和测试所提出的方法。本文发现,使用裁剪后的图像乘以2.16乘以对象的最大尺寸,可以显着加快处理时间,同时仍能提供较高的检测成功率,并且检测到的对象中心与实际中心相当接近。

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