Skip to content

Add a reference to the associated research paper #2

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
domportera wants to merge 1 commit into
base: master
Choose a base branch
from
Open

Add a reference to the associated research paper #2

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2,4 +2,4 @@
Pitch Pipe is a custom low-pass filter calibration technique that finds optimal parameters based on context specific information. As such, Pitch Pipe requires three inputs: a signal from which to derive relevant characteristics, a low-pass filter to calibrate, and an application specific criteria to optimize for, namely precision and lag. From the input device signal, Pitch Pipe extracts noise and maximum user speed estimates, which we use to generate synthetic noise and edge patterns. Thereafter, Pitch Pipe performs a grid search over the filter’s parameter space, evaluating its performance on the stated synthetic data. Pitch Pipe finally outputs the parameter set that best matches the application specific criteria. As such, Pitch Pipe internally comprises three steps that are to estimate noise, estimate maximum user speed, and optimize the parameter set.

## How To Cite
When using Pitch Pipe, please reference the following paper: [Coming Soon...]
When using Pitch Pipe, please reference the following paper: [Pitch Pipe: An Automatic Low-pass Filter Calibration Technique for Pointing Tasks](https://graphicsinterface.org/proceedings/gi2019/gi2019-27/)