C++ implementation of joint skeleton-surfaceShape EM-ICP
-
Updated
Jul 30, 2017 - C++
C++ implementation of joint skeleton-surfaceShape EM-ICP
A large collection of equations for Python 2 curve fitting and surface fitting that can output source code in several computing languages, and run a genetic algorithm for initial parameter estimation. Comes with cluster, parallel, IPython, GUI, NodeJS, and web-based graphical examples. Includes orthogonal distance and relative error regressions.
A large collection of equations for Python 3 curve fitting and surface fitting that can output source code in several computing languages, and run a genetic algorithm for initial parameter estimation. Comes with cluster, parallel, IPython, GUI, NodeJS, and web-based graphical examples. Includes orthogonal distance and relative error regressions.
Python 3 Bottle graphical curve fitting and surface fitting web application
Python 3 CherryPy graphical curve fitting and surface fitting web application
Python 3 Flask graphical curve fitting and surface fitting web application
A Django site in Python 2 for curve fitting 2D and 3D data that can output source code in several computing languages and run a genetic algorithm for initial parameter estimation. Includes orthogonal distance and relative error regressions. Generates PDF files and surface animations. Based on code from zunzun.com.
A Django site in Python 3 for curve fitting 2D and 3D data that can output source code in several computing languages and run a genetic algorithm for initial parameter estimation. Includes orthogonal distance and relative error regressions. Generates PDF files and surface animations. Based on code from zunzun.com.
Python 3 pyQt5 graphical curve fitting and surface fitting application, saves results to PDF
Python 3 wxPython graphical curve fitting and surface fitting application, saves results to PDF.
Python 3 tkinter graphical curve fitting and surface fitting application, saves results to PDF.
Matlab toolbox for creating 3D cave models from sparse survey
Given are two csv files, pc1.csv and pc2.csv, which contain noisy LIDAR point cloud data in the form of (x, y, z) coordinates of the ground plane. Find best surface fit
Neural nets for high accuracy multivariable nonlinear regression.
Estimating Ground Surface Normals and Fitting Surfaces to Noisy LIDAR Point Cloud Data
Examples and demos showing how to call functions from the NAG Library for Python
A Modern Fortran translation of the FITPACK package for curve and surface fitting
Add a description, image, and links to the surface-fitting topic page so that developers can more easily learn about it.
To associate your repository with the surface-fitting topic, visit your repo's landing page and select "manage topics."