Tracking and prediction of facial movement using the) RFD (river formation dynamics algorithm by Pythonlanguage

Authors

  • Muthana Mohammed, A.Prof.Dr. Akbas Ezaldeen Ali

Keywords:

This article details a Python-implemented River Formation Dynamics (RFD) algorithm face-tracking and prediction software mechanism. Performance requirements, resources, and development team expertise.

Abstract

This article details a Python-implemented River Formation Dynamics (RFD) algorithm face-tracking and prediction software mechanism. Performance requirements, resources, and development team expertise. Python is frequently the finest computer vision language due to its rich libraries, readability, and community support. Python syntax, data types, control structures, functions, and modules are covered. OpenCV's Haar sequence classifier and RFD algorithm demonstrate face detection, direction prediction, and tracking .recordeding two videos clipe, then divided into frames, marked with a green frame, and physically located by the Human Vision System (HVS). RFD tracking software accuracy was assessed by calculating the intersection area between the black and green frames. The results emphasise the significance of continual assessment methodology enhancement, including multiple test films and test settings, to improve RFD tracking technology efficiency and efficacy.

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Published

2024-02-28

How to Cite

Muthana Mohammed, A.Prof.Dr. Akbas Ezaldeen Ali. (2024). Tracking and prediction of facial movement using the) RFD (river formation dynamics algorithm by Pythonlanguage. Utilitas Mathematica, 120, 1311–1329. Retrieved from https://utilitasmathematica.com/index.php/Index/article/view/1885

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