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Study on extraction of image features of detectionand location based on video motion nuclear method

机译:基于视频运动核方法的检测定位图像特征提取研究

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complex applications, without and different target features directly affects the detection of selected tracking algorithm. So far still does not exist a universal algorithm for perfect can be suitable for various applications, so the detection and tracking of moving targets is still a valuable research subject of. The research work in this paper is in the field, the moving target detection spatiotemporal correlation and difference contour tracking algorithm based on a fixed background. The algorithm in the background under the condition of fixed to pay a smaller time complexity, the target detection and tracking has a good effect, so it has higher application value. Based on solving the detection and location of moving target tracking in real-time and accuracy requirements, a new moving target detection spatiotemporal correlation and difference contour tracking scheme based on the practical implementation, at the same time analysis and the experimental results are given. In the moving target tracking, tracking method is mainly traditional correlation method target based on template matching. The matching process is time consuming, so the actual use of more of the improved algorithm of correlation method, the improved algorithm attempts to improve the efficiency of feature matching and search range, and also achieved a certain effect, the some excellent tracking algorithm. This paper presents an improved active contour model tracking algorithm, improve the tracking efficiency and quality, the algorithm first from the frame difference detection results to find the moving target coarse contour, and then the convergence of coarse contour by using improved Snake algorithm, the right edge to get the target in the course of the campaign, in order to achieve the tracking of moving objects.
机译:复杂的应用,没有和不同的目标特征会直接影响所选跟踪算法的检测。到目前为止,还没有一种可以完美适用于各种应用的通用算法,因此运动目标的检测和跟踪仍然是有价值的研究课题。本文的研究工作是在现场,基于固定背景的运动目标检测时空相关和差分轮廓跟踪算法。该算法在固定背景下付出较小的时间复杂度,对目标的检测和跟踪效果良好,因此具有较高的应用价值。基于实时性和精度要求解决了运动目标跟踪的检测与定位问题,提出了一种基于实际实现的运动目标检测时空相关和差分轮廓跟踪方案,同时进行了分析和实验结果。在运动目标跟踪中,跟踪方法主要是基于模板匹配的传统相关方法目标。匹配过程是耗时的,因此实际使用更多的改进的相关算法算法,该改进算法试图提高特征匹配和搜索范围的效率,并且还取得了一定的效果,一些优秀的跟踪算法。本文提出了一种改进的主动轮廓模型跟踪算法,提高了跟踪效率和质量,该算法首先从帧差检测结果中找到运动目标的粗轮廓,然后利用改进的Snake算法收敛粗轮廓,右边在运动过程中获得目标,以实现对运动对象的跟踪。

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