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Detection and Tracking of Vehicle Target Based on Super-resolution Reconstruction and Variable Template Matching

机译:基于超分辨率重建和可变模板匹配的车辆目标检测与跟踪

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摘要

Vehicle target detection and tracking method based on image super-resolution reconstruction and variable template matching is put forward. Firstly, a nonlinear iterative algorithm is applied to reconstruct a super-resolution image from low resolution image sequence; then, the image is standardized and the movement areas are determined; finally, the variable template matching method is used to detect and track the vehicle targets in movement areas. From the characteristics of algorithm and the experiment results, we can see that the proposed algorithm improves the matching accuracy of target tracking and better solves the limitation of missed detection for traditional methods. The reason of the good performance of the proposed algorithm relies in high quality images acquired by super-resolution reconstruction from low resolution image sequence and the application of variable template matching method.
机译:提出了基于图像超分辨率重建和可变模板匹配的车辆目标检测和跟踪方法。首先,应用非线性迭代算法以从低分辨率图像序列重建超分辨率图像;然后,图像是标准化的,并且确定运动区域;最后,可变模板匹配方法用于检测和跟踪运动区域中的车辆目标。从算法的特点和实验结果,我们可以看出该算法提高了目标跟踪的匹配精度,更好地解决了对传统方法的错过检测的限制。所提出的算法的良好性能的原因依赖于由低分辨率图像序列的超分辨率重建获取的高质量图像和可变模板匹配方法的应用。

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