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Tracking Failure Detection Using Time Reverse Distance Error for Human Tracking

机译:使用时间反向距离误差进行人体跟踪的跟踪失败检测

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This paper proposes a tracking failure detection method based on time reverse error distance. Corner feature is used as interest point to perform the task. The algorithm consists of three stages. First, the corner feature is extracted from the image. Then, a tracker produces a trajectory by tracking the point in the previous frame to the current frame. Second, the location of point in the current frame is initialized as a reference point. The validated trajectory is obtained by tracking-reverse the reference point in the current frame to the previous frame. Third, both trajectories are compared with each other, if they are significantly different, the reversed point is considered as an incorrect. To evaluate the performance of this method, an object tracking method is performed. A set of points is initialized from a rectangular bounding box. These points are tracked and evaluated using the proposed tracking failure detection method. The correct tracked points are used to estimate bounding boxes in consecutive images. The performance results show that the proposed method is efficient for human detection and tracking in omnidirectional images.
机译:提出了一种基于时间反向误差距离的跟踪失效检测方法。角点功能用作执行任务的兴趣点。该算法包括三个阶段。首先,从图像中提取角特征。然后,跟踪器通过跟踪前一帧中的点到当前帧来生成轨迹。其次,将当前帧中的点的位置初始化为参考点。通过将当前帧中的参考点跟踪反向到前一帧来获得经过验证的轨迹。第三,将两个轨迹相互比较,如果它们明显不同,则将反转点视为不正确。为了评估此方法的性能,执行了对象跟踪方法。从矩形边界框初始化一组点。使用建议的跟踪故障检测方法对这些点进行跟踪和评估。正确的跟踪点用于估计连续图像中的边界框。性能结果表明,该方法对于全向图像中的人体检测和跟踪是有效的。

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