Playing a Computational Thinking Game using Hand Gestures

Castro, Elisa Marques de; Sakata, Tiemi C.; Zaina, Luciana A. M.

doi:10.1109/icalt.2019.00029

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2024

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“…In this Preprocessing to improve the process performance, prepare a model or image as not writable. As completed or trained the model then made a model or image as writable and covert back the RGB image to BGR image [13,14].…”

Section: Preprocessingmentioning

confidence: 99%

Gaming using different hand gestures using artificial neural network

Deena,

et al. 2024

EAI Endorsed Trans IoT

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INTRODUCTION: Gaming has evolved over the years, and one of the exciting developments in the industry is the integration of hand gesture recognition. OBJECTIVES: This paper proposes gaming using different hand gestures using Artificial Neural Networks which allows players to interact with games using natural hand movements, providing a more immersive and intuitive gaming experience. METHODS: Introduces two modules: recognition and analysis of gestures. The gesture recognition module identifies the gestures, and the analysis module assesses them to execute game controls based on the calculated analysis. RESULTS: The main results obtained in this paper are enhanced accessibility, higher accuracy and improved performance. CONCLUSION: To communicate with any of the traditional systems, physical contact is necessary. In the hand gesture recognition system, the same functionality can be interpreted by gestures without requiring physical contact with the interfaced devices.

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Section: Preprocessingmentioning

confidence: 99%

Gaming using different hand gestures using artificial neural network

Deena,

et al. 2024

EAI Endorsed Trans IoT

View full text Add to dashboard Cite

show abstract

Playing a Computational Thinking Game using Hand Gestures

Cited by 1 publication

References 13 publications

Gaming using different hand gestures using artificial neural network

Gaming using different hand gestures using artificial neural network

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