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novel face recognition transformational model and its inherent and optimal classification through a computationally efficient statistical algorithm
Title
A novel face recognition transformational model and its inherent and optimal classification through a computationally efficient statistical algorithm.
Creator
Kyperountas, Marios C., Florida Atlantic University, Erdol, Nurgun, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
This thesis is concerned with the development of a new face recognition method that has a high recognition performance and is computationally efficient, so that it can be applied to real time processes. A background research is presented, summarizing the most dominant face recognition methods, with an emphasis to the most popular statistical method, the 'Eigenfaces'. Initially, a new algorithm is developed based only on the computational efficiency criterion. It is simulated, and criterions...
Show moreThis thesis is concerned with the development of a new face recognition method that has a high recognition performance and is computationally efficient, so that it can be applied to real time processes. A background research is presented, summarizing the most dominant face recognition methods, with an emphasis to the most popular statistical method, the 'Eigenfaces'. Initially, a new algorithm is developed based only on the computational efficiency criterion. It is simulated, and criterions for achieving higher recognition rates are experimentally and theoretically determined. A new space transform is introduced, which enhances the algorithm's recognition capabilities. Its optimum classification measure is mathematically proven to be one that is inherently provided by the new face recognition algorithm. Finally, the developed method is evaluated, and experimentally compared against the 'Eigenfaces' method, using face data.
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Date Issued
2003
PURL
http://purl.flvc.org/fcla/dt/13034
Subject Headings
Human face recognition (Computer science), Eigenfunctions
Format
Document (PDF)
A Novel Method for Human Face Enhancement for Video Images
Title
A Novel Method for Human Face Enhancement for Video Images.
Creator
Salas, Ernesto Anel, Pandya, Abhijit S., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
The focus of this research is on images extracted from surveillance videos that have a low resolution and are taken under low illumination. In recent years, great advances have been made in face recognition and many studies mention results of 80% and 90% of recognition efficiency, however, most of these studies reported results using face images under controlled conditions. Current surveillance systems are equipped with low resolution cameras and are located in places with changing...
Show moreThe focus of this research is on images extracted from surveillance videos that have a low resolution and are taken under low illumination. In recent years, great advances have been made in face recognition and many studies mention results of 80% and 90% of recognition efficiency, however, most of these studies reported results using face images under controlled conditions. Current surveillance systems are equipped with low resolution cameras and are located in places with changing illumination, as opposed to a controlled environment. To be used in face recognition, images extracted from videos need to be normalized, enlarged and preprocessed. There is a multitude of processing algorithms for image enhancement, and each algorithm faces its advantages and disadvantages. This thesis presents a novel method for image enlargement of human faces applied to low quality video recordings. Results and comparison to traditional methods are also presented.
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Date Issued
2007
PURL
http://purl.flvc.org/fau/fd/FA00012547
Subject Headings
Human face recognition (Computer science), Biometric identification, Image processing--Digital techniques, Pattern recognition systems
Format
Document (PDF)
Face Processing Using Mobile Devices
Title
Face Processing Using Mobile Devices.
Creator
James, Jhanon, Marques, Oge, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
Image Processing and Computer Vision solutions have become commodities for software developers, thanks to the growing availability of Application Program- ming Interfaces (APIs) that encapsulate rich functionality, powered by advanced al- gorithms. To understand and create an e cient method to process faces in images by computers, one must understand how the human visual system processes them. Face processing by computers has been an active research area for about 50 years now. Face detection...
Show moreImage Processing and Computer Vision solutions have become commodities for software developers, thanks to the growing availability of Application Program- ming Interfaces (APIs) that encapsulate rich functionality, powered by advanced al- gorithms. To understand and create an e cient method to process faces in images by computers, one must understand how the human visual system processes them. Face processing by computers has been an active research area for about 50 years now. Face detection has become a commodity and is now incorporated into simple devices such as digital cameras and smartphones. An iOS app was implemented in Objective-C using Microsoft Cognitive Ser- vices APIs, as a tool for human vision and face processing research. Experimental work on image compression, upside-down orientation, the Thatcher e ect, negative inversion, high frequency, facial artifacts, caricatures and image degradation were completed on the Radboud and 10k US Adult Faces Databases along with other images.
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Date Issued
2016
PURL
http://purl.flvc.org/fau/fd/FA00004770, http://purl.flvc.org/fau/fd/FA00004770
Subject Headings
Image processing--Digital techniques., Mobile communication systems., Mobile computing., Artificial intelligence., Human face recognition (Computer science), Computer vision., Optical pattern recognition.
Format
Document (PDF)