Name
Abstract | ||
|---|---|---|
Hand shape is a natural and human-friendly interface for human-computer interaction. This paper proposes a real- time and 2D vision-based hand shape recognition method. The method is robust to hand pose changes because the hand pose is neutralized after recognizing a hand pose using distance transform, principal component analysis (PCA), and histogram analysis. Also, the context-based recognition method using shape decomposition can effectively recognize tiny changes of fingers. The method worked at 44.8 fps and had a recognition rate of 83% on average in the experiment with 800 images including 5 hand shapes and 16 hand poses. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ICIP.2011.6116497 | ICIP |
Keywords | Field | DocType |
computer vision,principal component analysis,user interfaces,gesture recognition,human computer interaction,image recognition,pose estimation,histograms,distance transform,image segmentation,shape | Computer vision,Histogram,Pattern recognition,Computer science,Gesture recognition,Pose,Image segmentation,Distance transform,Artificial intelligence,User interface,Principal component analysis | Conference |
ISSN | ISBN | Citations |
1522-4880 E-ISBN : 978-1-4577-1302-6 | 978-1-4577-1302-6 | 6 |
PageRank | References | Authors |
0.60 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Junyeong Choi | 1 | 37 | 4.03 |
| Hanhoon Park | 2 | 167 | 22.42 |
| Jong-Il Park | 3 | 465 | 67.34 |