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首页> 外文期刊>Journal of visual communication & image representation >Moving object detection and tracking from video captured by moving camera
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Moving object detection and tracking from video captured by moving camera

机译：从移动摄像机捕获的视频中检测移动目标并进行跟踪

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This paper presents an effective method for the detection and tracking of multiple moving objects from a video sequence captured by a moving camera without additional sensors. Moving object detection is relatively difficult for video captured by a moving camera, since camera motion and object motion are mixed. In the proposed method, the feature points in the frames are found and then classified as belonging to foreground or background features. Next, moving object regions are obtained using an integration scheme based on foreground feature points and foreground regions, which are obtained using an image difference scheme. Then, a compensation scheme based on the motion history of the continuous motion contours obtained from three consecutive frames is applied to increase the regions of moving objects. Moving objects are detected using a refinement scheme and a minimum bounding box. Finally, moving object tracking is achieved using a Kalman filter based on the center of gravity of a moving object region in the minimum bounding box. Experimental results show that the proposed method has good performance. (C) 2015 Elsevier Inc. All rights reserved.
机译：本文提出了一种有效的方法，该方法可以从运动摄像机捕获的视频序列中检测和跟踪多个运动对象，而无需附加传感器。对于移动摄像机捕获的视频而言，移动对象检测相对困难，因为摄像机运动和对象运动是混合的。在提出的方法中，找到帧中的特征点，然后将其分类为属于前景或背景特征。接下来，使用基于前景特征点和前景区域的积分方案，使用图像差分方案获得的运动对象区域。然后，基于从三个连续帧获得的连续运动轮廓的运动历史的补偿方案被应用于增加运动对象的区域。使用优化方案和最小边界框检测运动对象。最后，基于最小边界框中的运动对象区域的重心，使用卡尔曼滤波器实现运动对象跟踪。实验结果表明，该方法具有良好的性能。 （C）2015 Elsevier Inc.保留所有权利。

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