Name
Abstract | ||
|---|---|---|
We describe the design and evaluation of a freehand, smartwatch-based, mid-air pointing and clicking interaction technique, called Watchpoint. Watchpoint enables a user to point at a target on a nearby large display by moving their arm. It also enables target selection through a wrist rotation gesture. We validate the use of Watchpoint by comparing its performance with two existing techniques: Myopoint, which uses a specialized forearm mounted motion sensor, and a camera-based (Vicon) motion capture system. We show that Watchpoint is statistically comparable in speed and error rate to both systems and, in fact, outperforms in terms of error rate for small (high Fittsu0027s ID) targets. Our work demonstrates that a commodity smartwatch can serve as an effective pointing device in ubiquitous display environments. |
Year | Venue | Field |
|---|---|---|
2016 | AVI | Interaction technique,Computer vision,Motion capture,Wearable computer,Computer science,Gesture,Word error rate,Pointing device,Human–computer interaction,Artificial intelligence,Motion sensors,Smartwatch |
DocType | Citations | PageRank |
Conference | 7 | 0.66 |
References | Authors | |
8 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Keiko Katsuragawa | 1 | 17 | 4.48 |
| Krzysztof Pietroszek | 2 | 250 | 22.24 |
| James R. Wallace | 3 | 296 | 23.17 |
| Edward Lank | 4 | 729 | 60.44 |