一种利用主动形状模型进行轮廓跟踪的有效方法

A. Baumberg, David C. Hogg
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引用次数: 279

摘要

近年来,在实时轮廓跟踪和主动形状模型方面的研究引起了人们的极大兴趣。本文演示了动态滤波如何与基于模态的柔性形状模型结合使用,以跟踪运动中的铰接非刚体。结果表明,该方法可用于实时跟踪行走行人的轮廓。所使用的主动形状模型是由真实图像数据自动生成的,并且由于方向和物体的灵活性而包含形状的可变性。利用卡尔曼滤波控制空间尺度,对连续帧进行特征搜索。迭代细化允许在可行的情况下精确定位轮廓。形状模型结合了轮廓可能形状的知识,并通过减少系统参数的数量来加快跟踪速度。通过独立过滤形状参数,进一步提高了速度。
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An efficient method for contour tracking using active shape models
There has been considerable research interest recently, in the areas of real time contour tracking and active shape models. This paper demonstrates how dynamic filtering can be used in combination with a modal-based flexible shape model to track an articulated non-rigid body in motion. The results show the method being used to track the silhouette of a walking pedestrian in real time. The active shape model used was generated automatically from real image data and incorporates variability in shape due to orientation as well as object flexibility. A Kalman filter is used to control spatial scale for feature search over successive frames. Iterative refinement allows accurate contour localisation where feasible. The shape model incorporates knowledge of the likely shape of the contour and speeds up tracking by reducing the number of system parameters. A further increase in speed is obtained by filtering the shape parameters independently.<>
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