Deteksi Gerakan Kepala Secara Real-Time Menggunakan OpenCV Dan Python

Authors

  • Yusmita Imelda Universitas Negeri Medan, Indonesia
  • Leni Karmila Daulay Universitas Negeri Medan, Indonesia
  • Desni Paramitha Purba Universitas Negeri Medan, Indonesia
  • Hermawan Syahputra Universitas Negeri Medan, Indonesia

DOI:

https://doi.org/10.57235/jetbus.v2i1.6528

Keywords:

deteksi gerakan kepala, OpenCV, Python, landmark wajah, estimasi pose kepala, real-time

Abstract

Perkembangan teknologi komputer dan kecerdasan buatan telah mendorong inovasi dalam sistem interaksi manusia-komputer, salah satunya adalah deteksi gerakan kepala secara real-time. Penelitian ini bertujuan untuk mengembangkan sistem yang mampu mendeteksi dan mengklasifikasikan orientasi kepala (pitch, yaw, dan roll) dengan memanfaatkan pustaka OpenCV dan Dlib dalam bahasa pemrograman Python. Sistem dirancang dengan mengimplementasikan teknik deteksi wajah, pelacakan landmark, dan estimasi pose kepala menggunakan fungsi solvePnP. Hasil pengujian menunjukkan bahwa sistem mampu mendeteksi orientasi kepala secara akurat dan responsif dalam waktu kurang dari 0.5 detik. Evaluasi kinerja menunjukkan tingkat konsistensi yang baik, meskipun terdapat kendala pada kondisi pencahayaan rendah dan kualitas kamera yang kurang optimal. Aplikasi ini berpotensi untuk diterapkan dalam berbagai bidang seperti alat bantu disabilitas, sistem kontrol berbasis gestur, dan keamanan. Dengan pengembangan lanjutan, sistem ini dapat menjadi solusi interaktif yang lebih inklusif dan intuitif.

References

Bradski, G. (2000). The Opencv Library. Dr. Dobb's Journal Of Software Tools.

Dlib.Net. (2023). Dlib C++ Library.

Gonzalez, R. C., & Woods, R. E. (2018). Digital Image Processing (4th Ed.). Pearson Education.

Gupta, R., & Saini, A. (2021). Real-Time Face Detection And Attendance System Using Opencv. International Journal Of Computer Applications, 183(22), 25–29.Patel, M., Shah, R., & Vekariya, M. (2020). Real-Time Facial Expression Recognition Using Dlib And Machine Learning Algorithms. International Journal Of Scientific & Technology Research, 9(4), 420–425.

Kazemi, V., & Sullivan, J. (2014). One Millisecond Face Alignment With An Ensemble Of Regression Trees. Proceedings Of The Ieee Conference On Computer Vision And Pattern Recognition (Cvpr), 1867–1874.

King, D. E. (2009). Dlib-Ml: A Machine Learning Toolkit. Journal Of Machine Learning Research, 10(Jul), 1755–1758.

Murphy-Chutorian, E., & Trivedi, M. M. (2009). Head Pose Estimation In Computer Vision: A Survey. Ieee Transactions On Pattern Analysis And Machine Intelligence, 31(4), 607–626.

Numpy Developers. (2023). Numpy Documentation. Diakses Dari: Https://Numpy.Org/Doc/

Opencv.Org. (2023). Opencv Documentation. Diakses Dari: Https://Docs.Opencv.Org/

Zhang, K., Zhang, Z., Li, Z., & Qiao, Y. (2016). Joint Face Detection And Alignment Using Multi-Task Cascaded Convolutional Networks. Ieee Signal Processing Letters, 23(10), 1499–1503.

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Published

2025-06-27

How to Cite

Imelda, Y., Daulay, L. K., Purba, D. P., & Syahputra, H. (2025). Deteksi Gerakan Kepala Secara Real-Time Menggunakan OpenCV Dan Python. Journal of Education Transportation and Business, 2(1), 426–432. https://doi.org/10.57235/jetbus.v2i1.6528

Issue

Vol. 2 No. 1 (2025): Juni 2025

Section

Articles

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