Date: | November 18, 2009 |
---|---|
Location: | DC 1304 |
Time: | 1:30 |
Chair: | Matthew Thorne |
Date: | November 25, 2009 | December 2, 2009 | December 9, 2009 | December 16, 2009 |
---|---|---|---|---|
Location: | DC 1304 1:30 | DC 1304 1:30 | DC 1304 1:30 | DC 1304 1:30 |
Chair: | Cherry Zhang |
Areej Alhotali |
Martin Talbot |
Gabriel Esteves |
Technical Presentation: | Martin Talbot |
Michael Terry |
Matthew Thorne |
Cherry Zhang |
Jamie Ruiz |
Title : Effects of Target Size and Distance on Kinematic Endpoint Prediction
Abstract: In this talk, we present work extending previous work on kinematic endpoint prediction (KEP), a technique that uses models of user motion to predict endpoint in Fitts-style pointing tasks. We introduce a simplified algorithm to predict user end-point. We present a technique to measure the numerical stability of endpoint predictions in real time. We show that the distance of motion has a significant effect on predictor accuracy. Finally, we develop an accurate understanding of the relationship between movement distance and predictor accuracy and show how we can use this understanding to infer accurate, real-time probability distributions on target sets within an interface. Together, these results allow KEP to be applied in new and novel ways to pointing facilitation techniques. |
---|
Also see other Math and CS postings.