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FaRes: A Face Recognition System based on Motion Detection and Image Super Resolution
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 184 - Number 4 |
| Year of Publication: 2022 |
| Authors: Lionel Landry Sop Deffo, Elie Fute Tagne |
10.5120/ijca2022921997
|
Lionel Landry Sop Deffo, Elie Fute Tagne . FaRes: A Face Recognition System based on Motion Detection and Image Super Resolution. International Journal of Computer Applications. 184, 4 ( Mar 2022), 28-33. DOI=10.5120/ijca2022921997
Abstract
In Most implementations in recent computer applications include the processing of images and videos. They are therefore subject to many challenges notably the quality of images, the resources availability, variations in scene, etc. With the advent of deep learning approaches, the challenges faced have increased even further: this is because deep learning techniques are mostly based on artificial neural networks and as such, requires a lot of specific resources such as dedicated GPUs (graphical processing units). To cope with these challenges, solutions requiring less resource utilization are proposed. This passes through the inclusion of movement detection module leading to the restriction of further computations to only the zone of interest; that is, the area containing the element of interest (humans, cars, etc.). In addition, image enhancement modules are often used to increase the accuracy of the result. This paper proposes in an approach called FaReS: A face recognition system based on motion detection and image super resolution which uses a proposed improved moving object detection approach, adapted image enhancement and an adapted classification approach. It is assumed that environment considered is that where multimedia sensors such as IP cameras have been installed. The study is focused only on humans and not on all type of objects.
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