PENGIRAAN POSE MODEL MANUSIA PADA REPETISI KEBUGARAN AI PEMOGRAMAN PYTHON BERBASIS KOMPUTERISASI

Abstract Views : 1114 / Downloads Count: 1036

Authors

  • Muchlis Abdul Muthalib universitas malikussaleh
  • Irfan
  • Kartika universitas Malikussaleh
  • Selamat Meliala universitas Malikussaleh

DOI:

https://doi.org/10.31949/infotech.v9i1.4233

Keywords:

open cv, python, media pipe

Abstract

Pandemic people don't have free access to Gym. The importance of keeping the body fit. This can be overcome with the Human Pose Estimation Computer Vision technique. Optimum and maximum distance testing data. Webcam detects movement and test data on AI Fitness Counter models. Human Pose Estimation detection data is taken when someone does fitness exercises such as pull ups, pushups, and lifting weights. Optimal webcam detects Human Pose Estimation model AI Fitness Counter is three meters. Every detail of the landmarks in the pose corresponds to the key points of each limb and the utility lines that connect form the skeleton of the body. The application of the number of detection repetitions takes advantage of the angle of the elbow when it is straight and when it is bent. The angle forms 300 then a stage up occurs and is counted as one repetition. Meanwhile, when the angle forms 1700, a stage down occurs, and one repetition is counted as well. The use of Media pipe for the detection results is accurate and effective. This detection was successful because all members of the body were detected.

Downloads

Download data is not yet available.

References

H. Pardeshi, A. Ghaiwat, and A. Thongire. 2021. “Fitness Freaks : A System For Detecting Definite Body Posture Using Open Pose Estimation”. Mumbai

A. Anilkumar, A. K.T., S. Sajan, and S. K.A. 2021. “Pose Estimated Yoga Monitoring System,”. SSRN Electron. J., no. Icicnis, doi: 10.2139/ssrn.3882498. India: Ernakulam.

R. Josyula, S. Ostadabbas. 2021 “A Review on Human Pose Estimation,”. Northeastern University.

F. Zhang, Fan, Bazarevsky, Valentin, Vakunov, Andrey. 2020. “MediaPipe Hands: On-device Real-time Hand Tracking,”. USA: Mountain View CA 9403.

SR Sulistiyanti, FX. A. Setyawan, M. Komarudin. 2016 “Teaching Book of Image Processing”. Yogyakarta: Teknosain.

J. Utama. 2011. “Akuisisi Citra Digital menggunakan Pemrograman MATLAB”. Maj. Unikom. Vol. 9, no. 1, pp. 71–80.

M. M. Sobel, R. Canny, P. Teguh, K. Putra, N. Kadek, A. Wirdiani. 2016. “Pengolahan Citra Digital Deteksi Tepi Untuk Membandingkan Metode Sobel, Robert dan Canny”. J. Ilm. Merpati (Menara Penelit. Akad. Teknol. Informasi), vol. 2, no. 2, pp. 253–261.

A. Ahmad Hania. 2017. “Mengenal Artificial Intelligence, Machine Learning, & Deep Learning”. J. Teknol. Indones., vol. 1, no. June, pp. 1–6.

Syarifah, Fajriya. 2018. “Deep Learning Object Detection Pada Video Menggunakan Tensorflow dan CNN”. Yogyakarta: Universitas Islam Indonesia.

I. K. Setia Buana, 2018. “Aplikasi Untuk Pengoprasian Komputer Dengan Mendeteksi Gerakan Menggunakan Opencv Python”. Bali: STIKOM, pp. 190–191.

T. C. A.-S. Zulkhaidi, E. Maria, Y. Yulianto. 2020. “Pengenalan Pola Bentuk Wajah dengan OpenCV”. J. Rekayasa Teknol. Inf., vol. 3, no. 2, p. 181. Samarinda: Politeknik Pertanian.

S. S. Makahaube, A. M. Sambul, and S. R. U. Sompie. 2021. “Implementation of Gesture Recognition Technology for Automated Education Service Kiosk”. Vol. 16, no. 4, pp. 465–472. Manado: Universitas Sam Ratulangi.

Kartini, Good. 2020. “Deteksi Objek dan Kerusakan Daun Dengan Metode Pengolahan Citra Digital”. Laguboti: Institut Teknologi Del.

Hernández, Oscar G, Morell. 2021. “Human Pose Detection for Robotic-assisted and Rehabilitation Environments”. Spain: Uni- versity of Alicante.

C. Lugaresi, J. Tang, H. Nash. 2019. “Mediapipe: A Framework for Building Perception Pipelines”. Google Research.

N. Kikuchi, S. Yoshida, M. Okuyama. 2016. “The Effect of High-Intensity Interval Cycling Sprints Subsequent to Arm-Curl Exer- cise on Upper-Body Muscle Strength and Hypertrophy”. Tokyo: Nippon Sport Science University.

Zulfian Azmi. 2021. “Artificial Neural Network Model For Wind Mill”. Medan: STMIK Triguna Dharma.

I Gede Dharma Utayasa. 2021. “Efect Physical Activity and Nutrition During The Covid-19 Pandemic”. Surabaya: PGRI Adi Buana Surabaya University.

C. Creusot, N. Pears, J. Austin. 2013. “A machine-learning approach to keypoint detection and landmarking on 3D meshes”. Inter-

national Journal of Computer Vision, vol. 102, no 1-3, pp. 146-179.

A. Kitsikidis, K. Dimitropoulos, S. Douka, and N. Grammalidis. 2014.“Dance analysis using multiple kinect sensors,” in Proceed-ings of the 9th International Conference on Computer Vision Teory and Applications, VISAPP 2014, pp. 789 –795.

Downloads

Published

10-01-2023

How to Cite

Muthalib, M. A., Irfan, Kartika, & Meliala, S. (2023). PENGIRAAN POSE MODEL MANUSIA PADA REPETISI KEBUGARAN AI PEMOGRAMAN PYTHON BERBASIS KOMPUTERISASI. INFOTECH Journal, 9(1), 11–19. https://doi.org/10.31949/infotech.v9i1.4233

Issue

Section

Articles