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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >CamShift Tracking Method Based on Target Decomposition
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CamShift Tracking Method Based on Target Decomposition

机译:基于目标分解的CamShift跟踪方法

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In order to avoid the inaccurate location or the failure tracking caused by the occlusion or the pose variation, a novel tracking method is proposed based on CamShift algorithm by decomposing the target into multiple subtargets for location separately. Distance correlation matrices are constructed by the subtarget sets in the template image and the scene image to evaluate the correctness of the location results. The error locations of the subtargets can be corrected by resolving the optimization function constructed according to the relative positions among the subtargets. The directions and sizes of the correctly located subtargets with CamShift algorithm are updated to reduce the disturbance of the background in the tracking progress. Simulation results show that the method can perform the location and tracking of the target and has better adaptability to the scaling, translation, rotation, and occlusion. Furthermore, the computational cost of the method increases slightly, and its average tracking computational time of the single frame is less than 25 ms, which can meet the real-time requirement of the TV tracking system.
机译:为了避免定位不准确或由于遮挡或姿态变化引起的故障跟踪,提出了一种基于CamShift算法的跟踪方法,将目标分解为多个子目标分别进行定位。距离相关矩阵由模板图像和场景图像中的子目标集构成,以评估定位结果的正确性。通过解析根据子目标之间的相对位置构造的优化函数,可以校正子目标的错误位置。使用CamShift算法更新了正确定位的子目标的方向和大小,以减少跟踪过程中背景的干扰。仿真结果表明,该方法可以对目标进行定位和跟踪,对缩放,平移,旋转和遮挡具有更好的适应性。此外,该方法的计算成本略有增加,其单帧的平均跟踪计算时间小于25μms,可以满足电视跟踪系统的实时性要求。

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