Reading #3

Comments:

George
and some others


Summary

This paper mainly talked about the toolkit Quil, rather than recognition, the intimate goal of this tool is to advise designers on how to improve their gestures by warning the user if two gestures are too similar that can cause confusion.

First the author talks about how the similarity is built up, actually, a similarity model is learned from human judgments (three experiments and 49+49+266 participants). After an introduction of Quil's user interface, most of the paper talks about the difficulties and solution in UI, implementation and similarity metrics.



Discussion

Admittedly, the idea of building a gesture design tool is really fascinating, and many difficulties can be foreseen. However, I would like to see more discussion about how to build up the similarity metrics, this should be the core of the whole system and it is disappointing that the recognition only plays a small part in the whole system (I may need to check some previous paper from Long). Besides, the challenges and solutions (like timing and hierarchy) discussed in the paper I think are more related to AI.