Infrared face recognition

Konuk, Uğur
Face recognition is a leading biometrics technique that fulfills the increasing need to identify a person in today’s world. Face recognition also has broad range of utilization, such as commercial and law enforcement applications. That is the reason why it still gathers a lot of attention and is an active research topic. Nevertheless visible spectrum face recognition algorithms are not free of challenges. Illumination, pose, expression variances and existence of facial disguises still degrade the performance of recognition systems that utilize visible spectrum face images. That fact paved the way for infrared face recognition to emerge as an alternative solution to those limitations. In this thesis work, first a review of the infrared face recognition algorithms is presented. Four different methods, one of which is proposed for the first time in this thesis work, are implemented and compared in terms of recognition performance. The proposed method investigates the utilization of vascular network method with blood perfusion transform of the thermal data. Experiments are performed on Terravic and IRIS database.


Human body part detection and multi-human tracking in surveillance videos
Topçu, Hasan Hüseyin; Çiçekli, Fehime Nihan; Ulusoy, İlkay; Department of Computer Engineering (2012)
With the recent developments in Computer Vision and Pattern Recognition, surveillance applications are equipped with the capabilities of event/activity understanding and interpretation which usually require recognizing humans in real world scenes. Real world scenes such as airports, streets and train stations are complex because they involve many people, complicated occlusions and cluttered backgrounds. Although complex real world scenes exist, human detectors have the capability to locate pedestrians accur...
Face classification with support vector machine
Kepenekci, B; Akar, Gözde (2004-04-30)
A new approach to feature based frontal face recognition with Gabor wavelets and support vector machines is presented in this paper. The feature points are automatically extracted using the local characteristics of each individual face. A kernel that computes the similarity between two feature vectors, is used to map the face features to a space with higher dimension. To find the identity of a test face, the possible labels of each feature vector of that face is found with support vector machines, then the ...
A comparison of features spaces for face recognition problem
OZYER, Gulsah Tumuklii; Akbaş, Emre; Yarman Vural, Fatoş Tunay (2006-04-19)
One of the most important problems in face recognition problem is designing the feature space which represents human face the "best". Concatenating the popular feature sets together and forming a high dimensional vector introduces the curse of dimensionality problem. For this reason, feature selection is required in order to reduce the dimension of the feature space. In this study, popular feature sets used in face recognition literature are considered and comparison between these sets is done. Furthermore,...
Design of a feature set for face recognition problem
Akbaş, Emre (2006-11-03)
An important problem in face recognition is the design of the feature space which represents the human face. Various feature sets have been and are continually being proposed for this purpose. However, there exists no feature set which gives a superior and consistent recognition performance on various face databases. Concatenating the popular features together and forming a high dimensional feature space introduces the curse of dimensionality problem. For this reason, dimensionality reduction techniques suc...
Human action recognition for various input characteristics using 3 dimensional residual networks
Tüfekci, Gülin; Ulusoy, İlkay; Department of Electrical and Electronics Engineering (2019)
Action recognition using deep neural networks is a far-reaching research area which has been commonly utilized in applications such as statistical analysis of human behavior, detecting abnormalities using surveillance cameras and robotic systems. Previous studies have been performing researches to propose new machine learning algorithms and deep network architectures to obtain higher recognition accuracy levels. Instead of suggesting a network resulting in small accuracy gain, this thesis focuses on evaluat...
Citation Formats
U. Konuk, “Infrared face recognition,” M.S. - Master of Science, Middle East Technical University, 2015.