Extremely Low Quality Image Face Recognition
Name
Abdulateef Olamide Alli
Abstract
Image processing and analysis have evolved over the years into providing practical solutions to everyday challenges. The birth of new solutions and proposals also create new challenges usually surrounding the new innovations.
Existing face recognition algorithms have performed well and they have been deployed into solutions such as social media image tagging, mobile phone facial bio-metric authentication, immigration border control face matching among other solutions. The existing algorithms have been able to perform well in these scenarios because of the quality of the image from these use cases are usually of high quality with high resolution (HR) [1]. In other possible application of face recognition such as city camera surveillance, airport security surveillance and other related scenarios where image stream quality cannot be directly controlled or manipulated, it becomes imperative to seek a more robust solution that can deal with face recognition regardless of the frame size, lighting condition, race, age, pose and other varying factors that can significantly change the way the images are perceived by existing algorithms.
The goal of this thesis is to identify and test alternative methods of performing face recognition task in extremely low-quality images.
Existing face recognition algorithms have performed well and they have been deployed into solutions such as social media image tagging, mobile phone facial bio-metric authentication, immigration border control face matching among other solutions. The existing algorithms have been able to perform well in these scenarios because of the quality of the image from these use cases are usually of high quality with high resolution (HR) [1]. In other possible application of face recognition such as city camera surveillance, airport security surveillance and other related scenarios where image stream quality cannot be directly controlled or manipulated, it becomes imperative to seek a more robust solution that can deal with face recognition regardless of the frame size, lighting condition, race, age, pose and other varying factors that can significantly change the way the images are perceived by existing algorithms.
The goal of this thesis is to identify and test alternative methods of performing face recognition task in extremely low-quality images.
Graduation Thesis language
English
Graduation Thesis type
Master - Software Engineering
Supervisor(s)
Prof. Gholamreza Anbarjafari
Defence year
2019