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The aim is to explore recognizing QWERTY typing motions directly at the word level using a single RGB camera.

February 9, 2026Open Access

Word-Level Motion Learning for Contactless QWERTY Typing with a Single Camera

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The aim is to explore recognizing QWERTY typing motions directly at the word level using a single RGB camera.
Proposed a word-level contactless typing framework based on spatiotemporal finger motion patterns.
Utilized hand joint trajectories to model typing motions as distinctive patterns.
Implemented online learning with a trial-delayed adaptation protocol for motion prototypes.
Conducted experiments with vocabularies up to 200 words to evaluate recognition performance.
Achieved stable recognition performance at realistic typing speeds within the evaluated setup.
Demonstrated that learned motion representations can transfer from physical keyboards to flat surfaces.
Showed incremental learning of word-level motion patterns through repeated interactions.

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Demonstrates word-level typing recognition in constrained environments, suggesting a novel approach to text entry.

Yoo et al. (2026) studied this question.

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