Details

Autor(en) / Beteiligte

• Yafeng Yin
• Qun Li
• Lei Xie
• Shanhe Yi
• Novak, Edmund
• Sanglu Lu

Titel

CamK: A camera-based keyboard for small mobile devices

Ist Teil von

• IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications, 2016, p.1-9

Ort / Verlag

IEEE

Erscheinungsjahr

2016

Link zum Volltext

Quelle

IEEE Electronic Library (IEL)

Beschreibungen/Notizen

• 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.