Name
Abstract | ||
|---|---|---|
Stroke grouping in sketch recognition is both difficult and time-consuming. Our preliminary experiment indicates that, when people drawing flowcharts, their gaze focused on non-arrow areas, which providing a spatial cue for stroke grouping. Therefore, we present a novel stroke grouping method aided by gaze information. Based on gaze data that is collected simultaneously during natural drawing process, we generate hotspot areas serving as the position reference of semantic symbols. Strokes are first roughly grouped by the hotspot areas, so as to efficiently decrease the searching space. Experiment on a dataset of 54 flowcharts shows that time efficiency of stroke grouping can be greatly improved in our method and there is much potential for introducing eye-gaze data in sketch recognition. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1145/3025171.3025220 | IUI |
Keywords | Field | DocType |
Sketch recognition, stroke grouping, eye-hand coordination pattern, multimodal interaction | Multimodal interaction,Gaze,Computer science,Stroke,Human–computer interaction,Sketch recognition,Hotspot (Wi-Fi),Flowchart,Sketch | Conference |
Citations | PageRank | References |
1 | 0.35 | 10 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Beibei Chao | 1 | 1 | 0.35 |
| Xiaoyan Zhao | 2 | 1 | 1.02 |
| Dapeng Shi | 3 | 1 | 2.04 |
| Guihuan Feng | 4 | 67 | 5.98 |
| Bin Luo | 5 | 66 | 21.04 |