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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 7, 2021.
Abstract: Head Pose Estimation has always been an essential part for many applications such as autonomous driving and driv-ing assist systems and hence performance optimization provides better performance as well as lower computing and power needs that allows us to run such applications over embedded devices inside these systems. In this article we present an implementation over a Single board computer for a new system of 3D Head pose estimation that estimates the Head pose of a person in real-time for applications such as Driver monitoring systems, Drones, Gesture recognition and tracking devices. The system is developed over a single board computer (SBC) that is suitable for very low powered applications, it only utilizes the data provided through the IR camera sensor to estimate both the Head and camera pose without any need for external sensors. This system will combine methods that include traditional image processing techniques for image projection, feature detection, key point description and 3D pose estimation along with Machine Learning techniques for face detection and facial landmarks detection.
Emad Wassef, Hossam E. Abd El Munim, Sherif Hammad and Maged Ghoneima, “Robust Real-time Head Pose Estimation for 10 Watt SBC” International Journal of Advanced Computer Science and Applications(IJACSA), 12(7), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120766
@article{Wassef2021,
title = {Robust Real-time Head Pose Estimation for 10 Watt SBC},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120766},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120766},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {7},
author = {Emad Wassef and Hossam E. Abd El Munim and Sherif Hammad and Maged Ghoneima}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.