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
收藏
页码：448 / 459
页数：12
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