Computer Vision-Based Hand Recognition and Gesture Control for Dino Games
Hand Recognition and Gesture Control For Dino Game Using Computer Vision to control the popular Chrome Dino game using hand recognition and gesture control through computer vision techniques. The system leverages real-time image processing and machine learning algorithms to detect and interpret hand gestures, allowing for an intuitive and interactive gaming experience. The proposed method utilizes a webcam to capture live video feed, from which hand landmarks are extracted using a pre-trained neural network model. Various hand gestures, such as swipe and hold, are then mapped to corresponding in-game actions such as jumping and ducking. This gesture-based control mechanism not only enhances user engagement but also demonstrates the potential of computer vision in creating touchless interfaces for gaming applications.
Authors
- N. Senthamilarasi (ORCID: https://orcid.org/0000-0001-7314-3705)
- Chaganti Venkatarami Reddy
- Basavana Gowda Hosur Dinesh (ORCID: https://orcid.org/0000-0002-2306-4969)
Institutions
- Sathyabama Institute of Science and Technology (IN)
Publication Details
- Published
- 2025-03-05
- DOI
- https://doi.org/10.1109/esci63694.2025.10988141
- Primary Topic
- Hand Gesture Recognition Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00