Name
Abstract | ||
|---|---|---|
Due to the smaller size of mobile devices, on-screen keyboards become inefficient for text entry. In this paper, we present CamK, a camera-based text-entry method, which uses an arbitrary panel (e.g., a piece of paper) with a keyboard layout to input text into small devices. CamK captures the images during the typing process and uses the image processing technique to recognize the typing behavior. The principle of CamK is to extract the keys, track the user's fingertips, detect and localize the keystroke. To achieve high accuracy of keystroke localization and low false positive rate of keystroke detection, CamK introduces the initial training and online calibration. Additionally, CamK optimizes computation-intensive modules to reduce the time latency. We implement CamK on a mobile device running Android. Our experiment results show that CamK can achieve above 95% accuracy of keystroke localization, with only 4.8% false positive keystrokes. When compared to on-screen keyboards, CamK can achieve 1.25X typing speedup for regular text input and 2.5X for random character input. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/INFOCOM.2016.7524400 | IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications |
Keywords | Field | DocType |
camera-based keyboard,small-mobile devices,on-screen keyboards,text entry,camera-based text-entry method,CamK captures,image processing technique,user fingertips,keystroke localization accuracy,keystroke detection,online calibration,computation-intensive modules,Android,text input,random character input | False positive rate,Computer vision,Android (operating system),Keyboard layout,Computer science,CAMK,Image processing,Keystroke logging,Mobile device,Artificial intelligence,Embedded system,Speedup | Conference |
ISSN | ISBN | Citations |
0743-166X | 978-1-4673-9954-8 | 6 |
PageRank | References | Authors |
0.50 | 16 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yafeng Yin | 1 | 72 | 11.38 |
| Li Qun | 2 | 3443 | 245.59 |
| Lei Xie | 3 | 283 | 34.16 |
| Shanhe Yi | 4 | 139 | 7.80 |
| Edmund Novak | 5 | 118 | 7.50 |
| Sanglu Lu | 6 | 1380 | 144.07 |