SoloFinger: Robust Microgestures while Grasping Everyday Objects
| Autor: | Aditya Shekhar Nittala, Divyanshu Bhardwaj, Michael A. Hedderich, Bruno Fruchard, Daniel Ashbrook, Jess McIntosh, Dietrich Klakow, Jürgen Steimle, Adwait Sharma |
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| Rok vydání: | 2021 |
| Předmět: |
Commodity hardware
Computer science 05 social sciences 020207 software engineering 02 engineering and technology Object (computer science) Random forest Finger movement Robustness (computer science) Human–computer interaction 0202 electrical engineering electronic engineering information engineering Natural (music) 0501 psychology and cognitive sciences Classifier (UML) 050107 human factors Gesture |
| Zdroj: | CHI Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems |
| Popis: | Using microgestures, prior work has successfully enabled gestural interactions while holding objects. Yet, these existing methods are prone to false activations caused by natural finger movements while holding or manipulating the object. We address this issue with SoloFinger, a novel concept that allows design of microgestures that are robust against movements that naturally occur during primary activities. Using a data-driven approach, we establish that single-finger movements are rare in everyday hand-object actions and infer a single-finger input technique resilient to false activation. We demonstrate this concept’s robustness using a white-box classifier on a pre-existing dataset comprising 36 everyday hand-object actions. Our findings validate that simple SoloFinger gestures can relieve the need for complex finger configurations or delimiting gestures and that SoloFinger is applicable to diverse hand-object actions. Finally, we demonstrate SoloFinger’s high performance on commodity hardware using random forest classifiers. |
| Databáze: | OpenAIRE |
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