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...indow-based aggregation insensitive to window size in terms of computation time and accounts for the fast performance seen in realtime matchers [59, 64]. Figure 3: Shiftable window. The effect of trying all 3 × 3 shifted windows around the black pixel is the same as taking the minimum matching score across all centered (non-shifted) windows in the same neighborhood. (Only 3 of the neighboring shifted windows are shown here for clarity.) • Binomial filter: use a separable FIR (finite impulse response) filter. We use the coefficients 1/16{1, 4, 6, 4, 1}, the same ones used in Burt and Adelson’s [26] Laplacian pyramid. Other convolution kernels could also be added later, as could recursive (bi-directional) IIR filtering, which is a very efficient way to obtain large window sizes [35]. The width of the box or convolution kernel is controlled by aggr window size. To simulate the effect of shiftable windows [2, 18, 117], we can follow this aggregation step with a separable square min-filter. The width of this filter is controlled by the parameter aggr minfilter. The cascaded effect of a box-filter and an equal-sized min-filter is the same as evaluating a complete set of shifted windows, sinc...

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... matching strategy. The Laplacian 3 In the original paper [57] the authors used standard deviations of 5 in space and 1 frame in time.sBarron, Fleet and Beauchemin IJCV 12:1, pp43-77, 1994 10 pyramid =-=[13]-=- allows the computation of large displacements between frames and helps to enhance image structure, such as edges, that is often thought to be important. We begin at the coarsest level where displacem...

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...llow hues, orientation, and brightness) are extracted from the original color image at several spatial scales, using linear filtering. The different spatial scales are created using Gaussian pyramids =-=[33]-=-, which consist of progressively low-pass filtering and subsampling the input image. In our implementation, pyramids have a depth of 9 scales, providing horizontal and 2 (a) Central Representation WTA...

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..., then interpolated back up to the original resolution to form (a). The missing high frequency detail, (b) minus (a), is the \scene" to be estimated, (d) (this is the rst level of a Laplacian pyramid =-=[7]-=-). The low frequencies of (a) are removed to form the input bandpassed \image". We contrast normalize the image and scene by the local contrast of the input bandpassed image, yielding (c) and (d). Fig...

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...lass of "optimal" function, casting some doubt on the unique importance of Gabor's class of functions. 589 The basis functions of such a transform are related by dilation operations. Burt and Adelson =-=[5]-=- developed an efficient octave-width subband transform called the "Laplacian pyramid" and used it for image coding and other image processing tasks. An advantage of their technique is the computationa...