Unimanual Pen plus Touch Input Using Variations of Precision Grip Postures

被引：14

作者：

Cami, Drini ^{[1
]}

Matulic, Fabrice ^{[1
,2
]}

Calland, Richard G. ^{[2
]}

Vogel, Brian ^{[2
]}

Vogel, Daniel ^{[1
]}

机构：

[1] Univ Waterloo, Sch Comp Sci, Waterloo, ON, Canada

[2] Preferred Networks Inc, Tokyo, Japan

来源：

UIST 2018: PROCEEDINGS OF THE 31ST ANNUAL ACM SYMPOSIUM ON USER INTERFACE SOFTWARE AND TECHNOLOGY | 2018年

基金：

加拿大自然科学与工程研究理事会;

关键词：

pen input; touch input; interaction techniques;

D O I：

10.1145/3242587.3242652

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

We introduce a new pen input space by forming postures with the same hand that also grips the pen while writing, drawing, or selecting. The postures contact the multitouch surface around the pen to enable detection without special sensors. A formative study investigates the effectiveness, accuracy, and comfort of 33 candidate postures in controlled tasks. The results indicate a useful subset of postures. Using raw capacitive sensor data captured in the study, a convolutional neural network is trained to recognize 10 postures in real time. This recognizer is used to create application demonstrations for pen-based document annotation and vector drawing. A small usability study shows the approach is feasible.

引用

页码：825 / 837

页数：13