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Codes for "Predictive online optimisation with applications to optical flow"

Authors: Valkonen, Tuomo;

Codes for "Predictive online optimisation with applications to optical flow"

Abstract

These are the (Julia) codes for the optical flow experiments of the manuscript “Predictive online optimisation with applications to optical flow” by Tuomo Valkonen (arXiv:2002.03053). Prerequisites These codes were written for Julia 1.3. The Julia package prequisites are from November 2019 when our experiments were run, and have not been updated to maintain the same environment we used to do the experiments in the manuscript. You may get Julia from julialang.org. Using Navigate your unix shell to the directory containing this README.md and then run: $ julia --project=PredictPDPS The first time doing this, to ensure all the dependencies are installed, run $ ]instantiate Afterwards in the Julia shell, type: > using PredictPDPS This may take a while as Julia precompiles the code. Then, to generate all the experiments in the manuscript, run: > batchrun_article() This will save the results under img/. To see the experiments running visually, and not save the results, run > demo_known1() or any of demo_XY(), where X=1,2,3 and Y=known,unknown. Further parameters and experiments are available via run_experiments. See the source code for details. To run the data generation multi-threadeadly parallel to the algorithm, set the JULIA_NUM_THREADS environment variable to a number larger than one.

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Keywords

optical flow, online optimisation, primal-dual, nonsmooth

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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