eigen VS colmap

Is Eigen still alive? There's been no release in 3 years, and no news about it: https://gitlab.com/libeigen/eigen/-/issues/2699

I was curious about these libraries a few weeks ago and did some searching. Is there one that's got a clearly dominating set of users or contributors?

I don't know what a good way to compare these might be, other than perhaps activity/contributor count.

[1] https://github.com/simd-everywhere/simde

[2] https://github.com/ermig1979/Simd

[3] https://github.com/google/highway

[4] https://gitlab.com/libeigen/eigen

[5] https://github.com/shibatch/sleef

I am trying to include Eigen in my project via FetchContent. They define/assume-defined PROJECT_IS_TOP_LEVEL on line 19 and, among other locations, on line 607 in their top level list file.

Eigen is a header-only library, thus simply cloning it from the official repository into the FOGGDD folder should be enough.

math library because you should never implement a math library yourself, and you probably want somethign more focused on performance than STL. GLM may work if you just need basic vector support. Eigen may help for a more physics heavy game. But I'd probably find something in-between those two

cmake_minimum_required(VERSION 3.15) project(app) include(FetchContent) FetchContent_Declare(Eigen3 URL https://gitlab.com/libeigen/eigen/-/archive/3.4.0/eigen-3.4.0.tar.gz) FetchContent_MakeAvailable(Eigen3) add_executable(app main.cpp) target_link_libraries(app Eigen3::Eigen)

Today was very easy to do with Eigen

Not saying its easy to use, but there is an application gui and it is free: https://github.com/colmap/colmap

Colmap (Model folders (BIN and TXT), dense workspaces, NVM, PLY)

See colmap for example https://colmap.github.io/

You're looking into a problem called photogrammetry, and a well-studied one at that. I'd recommend looking into "shape from motion" (sfm); specifically techniques that do "dense reconstruction." I'd recommend COLMAP to start with. It does pose estimation from images (e.g. you point it at a bunch of images and it will figure out the relative poses of the cameras that took them), as well as sparse and dense reconstcution.

COLMAP builds dense meshes from a collection of cameras https://colmap.github.io/

I’ve seen references to using COLMAP (https://colmap.github.io/) to estimate camera position/pose, e.g. here

Classical photogrammetry, where I agree with u/tdgros that the way to go is https://colmap.github.io/. There are actually better variants in literature but nothing is more reliable and user-friendly than COLMAP. This will give you a very precise point cloud, that can be meshed if needed.