cleaned up some of the docs

This commit is contained in:
RodDeacon 2022-11-01 12:15:06 -07:00 committed by Zdzislaw Goik
parent 2cc2992388
commit 786e1b4143
3 changed files with 7 additions and 7 deletions

View File

@ -1,9 +1,9 @@
The goal of this project is to bring an easy to set up hardware and software wise, fast and accurate eye and/or mouth tracking solution for any headset that allows for mounting the eye tracking cameras and/or mouth tracking camera in or under the headset (in case of mouth tracking). The goal of this project is to bring an easy to set up hardware and software wise, fast and accurate eye and/or mouth tracking solution for any headset that allows for mounting the eye tracking cameras and/or mouth tracking camera in or under the headset (in case of mouth tracking).
It is also open source and open hardware meaning anyone can build it for them selfes and use it free of charge. It is also open source and open hardware meaning anyone can build it for themselves and use it free of charge.
This project is highly inspired by the excelent Full Body Trakcing solution - [SlimeVR](https://docs.slimevr.dev) This project is highly inspired by the excelent Full Body Tracking solution - [SlimeVR](https://docs.slimevr.dev)
and is aimging to do the same - make the eye and mouth tracking technology independted of the headset so that anyone can use it with anything they want and also make it cheaper. and is aimging to do the same - make the eye and mouth tracking technology independent of the headset so that anyone can use it with anything they want and also make it cheaper.
Goals in phases: Goals in phases:

View File

@ -7,12 +7,12 @@ The goal is to:
Now, having that out of the way, how should we process the data? It's being sent to us as an uncompressed stream from the ESP. Now, having that out of the way, how should we process the data? It's being sent to us as an uncompressed stream from the ESP.
We could use the OpenCV for image processing but what out detection? We could use the OpenCV for image processing, but what about detection?
DLib has a very good eye / face detection pre-trained model DLib has a very good eye / face detection pre-trained model
There are some ready-to-go solutions for openCV but won't they be too heavy? There are some ready-to-go solutions for openCV but won't they be too heavy?
How about training out own CNN model based on yey data sets? How about training our own CNN model based on eye datasets?
They would require labeling but they were used with great success by others. They would require labeling but they were used with great success by others.
Datasets - https://datagen.tech/blog/eye-datasets/ Datasets - https://datagen.tech/blog/eye-datasets/