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Moving Target Detection and Tracking Using Edge Features Detection and Matching

机译:使用边缘特征检测和匹配的运动目标检测和跟踪

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摘要

A new algorithm for fast detection and tracking of moving targets using a mobile video camera is presented. Our algorithm is based on image feature detection and matching. To detect features, we used edge points and their accumulated curvature. When the features are detected they are matched with their corresponding points using a new method called fuzzy-edge based feature matching. The proposed algorithm has two modes: detection and tracking. In the detection mode, background motion is estimated and compensated using an affine transformation. The resultant motion-rectified image is used for detection of the target location using split and merge algorithm. We also checked other features for precise detection of the target. When the target is identified, algorithm switches to the tracking mode, which also has two phases. In the first phase, the algorithm tracks the target with the intention to recover the target bounding-box more precisely and when the target bounding-box is determined precisely, the second phase of tracking algorithm starts to track the specified target more accurately. The algorithm has good performance in the environment with noise and illumination change.
机译:提出了一种使用移动摄像机快速检测和跟踪运动目标的新算法。我们的算法基于图像特征检测和匹配。为了检测特征,我们使用了边缘点及其累积的曲率。当检测到特征时,使用称为基于模糊边缘的特征匹配的新方法将它们与它们的对应点进行匹配。所提出的算法有两种模式:检测和跟踪。在检测模式下,使用仿射变换估计并补偿背景运动。生成的经过运动校正的图像用于使用拆分和合并算法检测目标位置。我们还检查了其他功能,以精确检测目标。确定目标后,算法将切换到跟踪模式,该模式也分为两个阶段。在第一阶段,该算法跟踪目标以更精确地恢复目标边界框,并且在精确确定目标边界框时,跟踪算法的第二阶段开始更精确地跟踪指定目标。该算法在噪声和照度变化的环境中具有良好的性能。

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