https://github.com/csukuangfj/code-for-lucas-kanade-20-years-on

https://github.com/csukuangfj/code-for-lucas-kanade-20-years-on

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• Host: GitHub
• URL: https://github.com/csukuangfj/code-for-lucas-kanade-20-years-on
• Owner: csukuangfj
• Created: 2016-07-10T19:19:54.000Z (almost 9 years ago)
• Default Branch: master
• Last Pushed: 2017-10-08T15:06:13.000Z (over 7 years ago)
• Last Synced: 2025-03-30T15:36:44.865Z (about 2 months ago)
• Language: C
• Size: 9.17 MB
• Stars: 70
• Watchers: 1
• Forks: 40
• Open Issues: 0
• Metadata Files:
  • Readme: README-lk20p1.txt

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README

        
Lucas-Kanade 20 Years On: A Unifying Framework

Part 1: The Quantity Approximated, the Warp Update Rule and the Gradient

Descent Approximation

Simon Baker and Iain Matthews

The Robotics Institute

Carnegie Mellon University

Pittsburgh, PA 15213

USA

Contact: [email protected], [email protected]

---------------------------------------------------------------------------

URL: http://www.ri.cmu.edu/projects/project_515.html

Bibtex reference:

@article{Baker_2004_4293,

	author = "Simon Baker and Iain Matthews",

	title = "Lucas-Kanade 20 Years On: A Unifying Framework Part 1: The Quantity Approximated, the Warp Update Rule, and the Gradient Descent Approximation",

	journal = "International Journal of Computer Vision",

	year = "2004"

}

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                             MATLAB SOURCE CODE

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The source code is split into two directories, both need to be added to your

Matlab search path:

lk20-p1           The algorithms described in the paper and test scripts

lk20-common       Common code for all algorithms (and for later papers)

lk20-p1/

--------

The Gauss-Newton affine warp algorithms in Section 3 of the paper are:

affine_fa.m       Forwards-Additive

affine_fc.m       Forwards-Compositional

affine_ia.m       Inverse-Additive

affine_ic.m       Inverse-Compositional

The Gauss-Newton projecive warp algorithms in Section 3 of the paper are:

homo_fa.m         Forwards-Additive

homo_fc.m         Forwards-Compositional

homo_ic.m         Inverse-Compositional

Note: the inverse-additive algorithm cannot be applied with a projective warp.

The additional algorithms from Section 4 of the paper are:

affine_ic_nt.m    Inverse-Compositional Newton (4.2)

affine_ic_sd.m    Inverse-Compositional Steepest Descent (4.3)

affine_ic_d.m     Inverse-Compositional with diagonal Hessian (4.4)

affine_ic.nt_d.m  Inverse-Compositional Newton with diagonal Hessian (4.4)

affine_ic_lm.m    Inverse-Compositional Levenburg-Marquardt (4.5)

To run the perturbation experiments described in the paper examine:

run_affine.m       Run an affine warp experiment

run_homo.m         Run a projective warp experiment

These files should be edited for the experimental parameters you would like to

test. By default they run everything for a few tests. To replicate the

experiments in the paper run each algorithm for 100 convergence tests and 1000

frequency of convergence tests. This will take some time!

lk20p1/data/

------------

The data directory contains precomputed random perturbation data (for

experimental consistency) and the images and template definitions.

lk20p1/figures/

---------------

The figures directory contains matlab scripts for plotting your results and

creating graphs similar to those shown in the paper.