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Removes noise from the Kinect Depth Frames in real-time using pixel filters and weighted moving average technique

depthframe kinect smoothingSmart filter to remove Floyd-Steinberg dithering from paletted images.The tool analyses image palette to find optimal blurring threshold. For any two adjacent pixels, if the palette has a color that is between colors of these two pixels, then it's assumed to be an edge.

paletted-images palette smoothing dithering smart-blur reconstructionChaikin's smoothing algorithm for 2D polylines.Performs the smoothing algorithm on the specified path, returning a list populated with the additional smoothed points. If the input path has a length of <= 2, the result will be a new array with the same points as the input.

chaikin smooth polyline 2d polygon smoothing chaikin's smoother algorithm svg shape round subdivide points line pathComputes the Laplacian of a mesh. Constructs the mesh Laplacian for a given surface mesh using barycentric cotangent weights.

mesh laplacian differential discrete geometry cell simplicial complex surface smoothing calculusGiven input data xs, a kernel function and a bandwidth (if not supplied, a default value of 0.5 is used), this function returns a basic kernel density estimator: a function of one variable, x, which when invoked returns the kernel density estimate for x. The returned function can also be called with a vector supplied as an argument for x. In this case, the density is evaluated is for each element of the vector and the vector of density estimates is returned. Given input predictors xs and observed responses ys, a kernel function and a bandwidth (if not supplied, a default value of 0.5 is used), this function returns the Nadaraya & Watson kernel regression estimator: a function of one variable, x, which when invoked returns the estimate for y. The returned function can also be called with a vector supplied as an argument for x. In this case, predictions are generated for each element of the vector and the vector of predictions is returned.

statistics nonparametrics kernel smoothingSPLINTER (SPLine INTERpolation) is a library for multivariate function approximation with splines. The library can be used for function approximation, regression, data smoothing, data reduction, and much more. Spline approximations are represented by a speedy C++ implementation of the tensor product B-spline. The B-spline consists of piecewise polynomial basis functions, offering a high flexibility and smoothness. The B-spline can be fitted to data using ordinary least squares (OLS), possibly with regularization. The library also offers construction of penalized splines (P-splines).

b-splines splines function-approximation interpolation p-spline c-plus-plus smoothingMoving average smoothing, replaces each point in the array with the average of "x" adjacent points

javascript-array smoothing smooth arraySmart filter to remove Floyd-Steinberg dithering from paletted images. The tool analyses image palette to find optimal blurring threshold. For any two adjacent pixels, if the palette has a color that is between colors of these two pixels, then it's assumed to be an edge.

paletted-images palette smoothing dithering smart-blur reconstructionPlease consult the ASAP demo site or our VLDB 2017 paper for details.

visualization time-series smoothing:wavy_dash: Smoothing algorithm for 2D lines and polygons

smooth smooth-polygon smooth-polyline 2d-graphics 2d-graph-functions chaikin chaikin's smoothing polyline polygon 2d svg canvas algorithm shape round points line path
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