Description: 包含了5篇Tony Lindeberg 尺度空间理论经典著作，希望大家能够受益-Contains five Tony Lindeberg Scale Space Theory classics, I hope we can benefit from Platform: |
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Description: 在基于Mean-Shift的目标跟踪算法中，尺度自适应机制是算法研究的一个重要方向。一种典型的方法采
用Lindeberg的尺度空间理论以获取目标尺度信息。但现有算法中将尺度由2．D矢量压缩为1一D量，未能精细地
刻画目标仿射变换时的尺度变化，从而限制了算法的适用范围。为此，该文将尺度维1．D滤波推广至2一D，构造得
到了相应的垂D尺度空间，并利用窄间维和尺度维的Mean-Shift交替迭代，实现了同时在空间位置和尺度方向对
目标的有效跟踪，提高了算法在目标尺度变化时的自适应性，并扩大了算法的适用范围。
关键-Scale adaptive mechanism in the target tracking algorithm based on Mean-Shift algorithm is an important direction of research. A typical method using Lindeberg' s scale space theory to obtain the target scale. However, the existing algorithms will scale from 2. D vector compression for 1-D volume, not fine to portray the target affine transformation of scale changes, thus limiting the scope of application of the algorithm. To this end, the paper will scale dimension. D filter to the 2-D structure has been the vertical D scale space and the use of narrow inter-dimension and scale dimension of the Mean-Shift alternating iteration, effective tracking of the target position in space and scale direction to improve the self-adaptive algorithm when the target scale changes, and to expand the scope of application of the algorithm. Key Platform: |
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Description: SIFT算法是在不同的尺度空间上查找关键点,而尺度空间的获取需要使用高斯模糊来实现,Lindeberg等人已证明高斯卷积核是实现尺度变换的唯一变换核-SIFT algorithm is to find the key points on the different scales of space and capture scale space requires the use of a Gaussian blur to achieve, Lindeberg, who has proved a Gaussian convolution kernel is the only transform kernel to achieve scale transformation Platform: |
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