Fast Dynamic Programming for Elastic Registration of Curves

Description

This is a software suite for computing optimal diffeomorphisms for elastic registration of curves. Algorithm adapt-DP is based on DP (dynamic programming) restricted to an adapting strip which is able to perform this computation in linear time. Description of Algorithm adapt-DP can be found in "Fast Dynamic Programming for Elastic Registration of Curves", Proceedings of the 2nd International Workshop on Differential Geometry in Computer Vision and Machine Learning (DIFF-CVML'16) in conjunction with Computer Vision Pattern Recognition Conference (CVPR) 2016, Las Vegas, Nevada, June 26-July 1, 2016. The zip file Fast_Dynamic_Programming.zip contains copies of implementation of Algorithm adapt-DP as Fortran files (a Matlab Fortran mex file and a Python compatible Fortran file) for execution with Matlab/Python, Matlab/Python test files for executing adapt-DP Matlab Fortran mex file and Python compatible Fortran file, respectively, example data files, usage instructions in README files, etc.

Resources

Name Format Description Link
0 Hash of the data file https://data.nist.gov/od/ds/6FCA2C44E87B3E49E05324570681DCB11939/Fast_Dynamic_Programming.zip.sha256
21 DOI Access to Fast Dynamic Programming for Elastic Registration of Curves https://doi.org/10.18434/T4/1502501
57 zip file with copies of implementation of Algorithm adapt-DP as Fortran files (a Matlab Fortran mex file and a Python compatible Fortran file) for execution with Matlab/Python, Matlab/Python test file for executing adapt-DP Matlab Fortran mex file and Python compatible Fortran file, respectively, example data files, usage intructions in README files, etc. Algorithm adapt-DP is based on DP (dynamic programming) restricted to an adapting strip for computing in linear time optimal diffeomorphisms for elastic registration of curves. Description of Algorithm adapt-DP can be found in "Fast Dynamic Programming for Elastic Registration of Curves", Proceedings of the 2nd International Workshop on Differential Geometry in Computer Vision and Machine Learning (DIFF-CVML'16) in conjunction with Computer Vision Pattern Recognition Conference (CVPR) 2016, Las Vegas, Nevada, June 26-July 1, 2016. https://math.nist.gov/~JBernal/Fast_Dynamic_Programming.zip
0 zip file with copies of implementation of Algorithm adapt-DP as Fortran files (a Matlab Fortran mex file and a Python compatible Fortran file) for execution with Matlab/Python, Matlab/Python test file for executing adapt-DP Matlab Fortran mex file and Python compatible Fortran file, respectively, example data files, usage intructions in README files, etc. Algorithm adapt-DP is based on DP (dynamic programming) restricted to an adapting strip for computing in linear time optimal diffeomorphisms for elastic registration of curves. Description of Algorithm adapt-DP can be found in "Fast Dynamic Programming for Elastic Registration of Curves", Proceedings of the 2nd International Workshop on Differential Geometry in Computer Vision and Machine Learning (DIFF-CVML'16) in conjunction with Computer Vision Pattern Recognition Conference (CVPR) 2016, Las Vegas, Nevada, June 26-July 1, 2016. https://data.nist.gov/od/ds/6FCA2C44E87B3E49E05324570681DCB11939/Fast_Dynamic_Programming.zip

Tags

  • dynamic-programming
  • shape-analysis
  • elastic-registration
  • adapting-strip

Topics

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