# Julia frameworks for large-scale nonlinear least-squares optimization for computer vision

**URL:** <https://discourse.julialang.org/t/julia-frameworks-for-large-scale-nonlinear-least-squares-optimization-for-computer-vision/49344>\
**Category:** Optimization (Mathematical)\
**Tags:** question, machinevision, optimization\
**Created:** [October 30, 2020, 11:45pm UTC](https://discourse.julialang.org/t/julia-frameworks-for-large-scale-nonlinear-least-squares-optimization-for-computer-vision/49344 "2020-10-30T23:45:59Z")\
**Posts on this page:** 1\
**Showing post:** 4

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**Author:** ![user664303](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/user664303/32/37843_2.png) [@user664303](https://discourse.julialang.org/u/user664303)\
**Post date:** [March 21, 2024, 10:42am UTC](https://discourse.julialang.org/t/julia-frameworks-for-large-scale-nonlinear-least-squares-optimization-for-computer-vision/49344/4 "2024-03-21T10:42:44Z")

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I wrote two packages that together can do bundle adjustment (and other such optimizations) very efficiently:

[NLLSsolver.jl](https://github.com/ojwoodford/NLLSsolver.jl) - A non-linear least squares solver that supports sparse problems, auto-differentiation, and robustified costs.

[VisualGeometryOptimization.jl](https://github.com/ojwoodford/VisualGeometryOptimization.jl) - This package constructs visual geometry optimization problems that can then be solved by NLLSsolver.

I am [seeking collaborators](https://discourse.julialang.org/t/collaboration-call-photometric-methods-for-visual-tracking/111926) to further extend the functionality of the second package.

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