Exploring Gesture-Based Interaction in Smartwatch Games: A Comparative Study Between Continuous Gesture Recognition and Hidden Markov Models

被引：0

作者：

Silva, Leonardo ^{[1
]}

Fernandes, Deborah ^{[2
]}

Nogueira, Emilia ^{[2
]}

Felix, Juliana ^{[2
]}

Cardoso, Luciana ^{[1
]}

Aranha, Renan ^{[3
]}

Nascimento, Thamer Horbylon ^{[1
]}

Soares, Fabrizzio ^{[2
]}

机构：

[1] Fed Inst Goiano, Campus Ipora, Ipora, Goias, Brazil

[2] Univ Fed Goias, Inst Informat, Goiania, Go, Brazil

[3] Univ Fed Mato Grosso, Cuiaba, Goias, Brazil

来源：

ADVANCES IN VISUAL COMPUTING, ISVC 2024, PT II | 2025年 / 15047卷

关键词：

Smartwatches Gesture interaction; Continuous gesture recognition; Hidden Markov Models (HMM); Games;

D O I：

10.1007/978-3-031-77389-1_35

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This work presents the evaluation of two interaction techniques in games using a smartwatch as a control device: On-screen Continuous Gesture Recognition and air gestures with HMM. The experiment involved participants, aged between 17 and 50 years old. The results indicated a clear preference for the On-screen Continuous Gesture Recognition technique, highlighting its effectiveness and acceptance by users. The analysis of the System Usability Scale (SUS) results showed a positive evaluation for this technique, while the HMM technique was considered less favorable for endless running games. Participants showed a preference for the on-screen touch approach, emphasizing its intuitiveness and satisfactory interaction experience. The findings suggest that On-screen Continuous Gesture Recognition provides a smoother and more natural interaction compared to air gestures with HMM.

引用

页码：448 / 459

页数：12

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