Summary
In this paper, Li introduces his gesture recognizer named Protractor. It works similar to the $1 Recognizer presented by Wobbrock but is faster and can be made to be orientation-sensitive. Protractor first resamples to N points and then rotates based on the indicative angle or to one of eight orientations if it is specified to be orientation-sensitive. It then calculates the optimal angular distance against each template and returns the top choice of the N-best list of results.
Discussion
Protractor uses the same concepts presented in the $1 Recognizer but also makes some key improvements. Protractor is able to recognize gesture which are orientation-sensitive by only rotating to certain angles and not scaling to avoid distorting the input. It also uses a closed-form solution to find the rotation that leads to the minimum angular distance instead of using the iterative approach utilized in $1. This helps Protractor to produce a higher accuracy in shorter amounts of time.