Gestures a Go Go: Authoring Synthetic Human-Like Stroke Gestures Using the Kinematic Theory of Rapid Movements

被引:33
作者
Leiva, Luis A. [1 ]
Martin-Albo, Daniel [1 ]
Plamondon, Rejean [2 ]
机构
[1] Univ Politecn Valencia, PRHLT Res Ctr, E-46022 Valencia, Spain
[2] Ecole Polytech, Lab Scribens, Dept Genie Elect, 6079 Succursale Ctr Ville, Montreal, PQ H3C 3A7, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Algorithms; Design; Human Factors; Gesture synthesis; bootstrapping; gesture recognition; strokes; marks; symbols; unistrokes; multistrokes; multitouch; kinematics; user interfaces; rapid prototyping; REPRESENTATION; RECOGNITION;
D O I
10.1145/2799648
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Training a high-quality gesture recognizer requires providing a large number of examples to enable good performance on unseen, future data. However, recruiting participants, data collection, and labeling, etc., necessary for achieving this goal are usually time consuming and expensive. Thus, it is important to investigate how to empower developers to quickly collect gesture samples for improving UI usage and user experience. In response to this need, we introduce Gestures a Go Go (G3), a web service plus an accompanying web application for bootstrapping stroke gesture samples based on the kinematic theory of rapid human movements. The user only has to provide a gesture example once, and G3 will create a model of that gesture. Then, by introducing local and global perturbations to the model parameters, G3 generates from tens to thousands of synthetic human-like samples. Through a comprehensive evaluation, we show that synthesized gestures perform equally similar to gestures generated by human users. Ultimately, this work informs our understanding of designing better user interfaces that are driven by gestures.
引用
收藏
页数:29
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