Implementasi Posenet Dalam Game Semaphore Untuk Mengenali Gerakan Tubuh Pengguna

Baby Aisha Maritza Virginia, Anis Cherid

Abstract


Saat ini, pembelajaran semaphore masih dilakukan secara manual dengan bimbingan instruktur, yang memiliki keterbatasan dalam ketersediaan instruktur dan efisiensi waktu. Penelitian ini bertujuan untuk membuat game semaphore yang mengimplementasikan PoseNet untuk meningkatkan efisiensi dan interaktivitas pembelajaran gestur semaphore. Melalui penerapan teknologi PoseNet, game ini bertujuan untuk mengenali gerakan tubuh pengguna secara real-time. Dengan mengidentifikasi 17 titik kunci pada tubuh manusia, PoseNet memungkinkan deteksi gestur semaphore secara otomatis dan secara real-time. Metode dan model pengembangan sistem yang digunakan adalah model prototipe & MDLC, dan penerapan library p5.js dan ml5.js memberikan basis untuk integrasi PoseNet ke dalam game Semaphore. Hasil penelitian ini menyajikan game semaphore yang mengimplementasikan PoseNet sebagai solusi inovatif untuk meningkatkan pembelajaran gestur semaphore.

Keywords


semaphore; posenet; body recognition; interactive game

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References


“Teach-AI-to-Dance-with-PoseNet,” GitHub, 2023. [Online]. Available: https://github.com/znreza/Teach-AI-to-Dance-with-PoseNet

“Awesome Dancing with AI Tutorial,” GitHub, 2023. . [Online]. Available: https://github.com/dancingwithai/dancingwithai.github.io

“google-coral/project-posenet,” GitHub, 2023. [Online]. Available: https://github.com/google-coral/project-posenet

“Human Pose Classification with MoveNet and TensorFlow Lite,” TensorFlow, 2023. https://www.tensorflow.org/lite/tutorials/pose_classification

Bhosale, Pranjal, & Bale. “Yoga Pose Detection and Correction using Posenet and KNN,” Research Gate . [Online]. Available: https://www.researchgate.net/publication/360950640_Yoga_Pose_Detection_and_Correction_using_Posenet_and_KNN

D. Shah, V. Rautela, C. Sharma and A. Florence A, "Yoga Pose Detection Using Posenet and k-NN," 2021 International Conference on Computing, Communication and Green Engineering (CCGE), Pune, India, 2021, pp. 1-4, doi: 10.1109/CCGE50943.2021.9776451. . [Online]. Available: https://ieeexplore.ieee.org/document/9776451

“Yoga Pose Estimation using POSENET vision model,” GitHub, 2023. [Online]. Available: https:// github.com/Anjanapradeep/POSE_ESTIMATION-YOGA-POSES

“PoseNet: Revolutionizing Human Pose Estimation with Deep Learning,” Medium, 2023. [Online]. Available: https://medium.com/aimonks/posenet-revolutionizing-human-pose-estimation-with-deep-learning-1eecbc873966

“Evaluation of PoseNet for applied AI-Fitness applications,” Medium, 2023. [Online]. Available: https://medium.com/optima-ai/evaluation-of-posenet-for-applied-ai-in-fitness-applications-56de98d6c4e4

“Selecting Your Real-Time Pose Estimation Models,” Medium, 2023. [Online]. Available: https://maureentkt.medium.com/selecting-your-2d-real-time-pose-estimation-models-7d0777bf935f

Davids Joe (2022). Artificial Intelligence for Physiotherapy and Rehabilitation Research Gate . [Online]. Available: https://link.springer.com/referenceworkentry/10.1007/978-3-030-64573-1_339

Chung, J. L., Ong L. Y., & Chew L. M. (2022). Comparative Analysis of Skeleton Based Human Pose Estimation, Research Gate [Online]. Available: https://www.mdpi.com/1999-5903/14/12/380

“7 Popular AI Projects On Gesture Gaming,” Analytics India Magazine, 2023. [Online] Available: https://analyticsindiamag.com/7-popular-ai-projects-on-gesture-gaming/

“Body movement recognition in the ‘Smart Baduanjin’ App,” Medium, 2023. [Online]. Available: https://medium.com/tensorflow/body-movement-recognition-in-the-smart-baduanjin-app-2a4e2d5159c8

“Body Detection using Computer Vision,” Medium, 2023. [Online]. Available: https://medium.com/instrument-stories/body-detection-with-computer-vision-1898cdc6b7d

Syahrul, A. M. ., & Rahayu, M. I. (2019). Aplikasi Game “Semaphore” Berbasis Android. Jurnal Teknologi Informasi Dan Komunikasi, 8(1), 1–10. [Online]. Available: https://doi.org/10.58761/jurtikstmikbandung.v8i1.121

J. D. Santos Rivera, “Making a game with PoseNet, a pose estimator model,” in Practical TensorFlow.js, SpringerLink, pp. 125-149, Sep. 2020. [Online]. Available: https://doi.org/10.1007/978-1-4842-6168-7_6




DOI: https://dx.doi.org/10.36080/bit.v21i1.2691

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