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+/**
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+@page getting-started Getting started
+
+
+Welcome to the OpenVINS project!
+The following guides will help new users through the downloading of the software and running on datasets that we support.
+Additionally, we provide information on how to get your own sensors running on our system and have a guide on how we perform calibration.
+Please feel free to open an issue if you find any missing or areas that could be clarified.
+
+
+@section highlevel High-level overview
+
+From a high level the system is build on a few key algorithms.
+At the center we have the ov_core which contains a lot of standard computer vision algorithms and utilities that anybody can use.
+Specifically it stores the following large components:
+
+- Sparse feature visual tracking (KLT and descriptor-based)
+- Fundamental math types used to represent states
+- Initialization procedures
+- Multi-sensor simulator that generates synthetic measurements
+
+
+This ov_core library is used by the ov_msckf system which contains our filter-based estimator.
+Within this we have the state, its manager, type system, prediction, and update algorithms.
+We encourage users to look at the specific documentation for a detailed view of what we support.
+The ov_eval library has a bunch of evaluation methods and scripts that one can use to generate research results for publication.
+
+
+
+
+
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+@section getting-started-more Getting Started Guides
+
+-   @subpage gs-installing --- Installation guide for OpenVINS and dependencies
+-   @subpage dev-docker --- Installing with Docker instead of from source
+-   @subpage gs-tutorial --- Simple tutorial on getting OpenVINS running out of the box.
+-   @subpage gs-datasets --- Links to supported datasets and configuration files
+-   @subpage gs-calibration --- Guide to how to calibration your own visual-inertial sensors.
+
+
+
+*/