A comparison of features spaces for face recognition problem

Date

2006-04-19

Author

OZYER, Gulsah Tumuklii
Akbaş, Emre
Yarman Vural, Fatoş Tunay

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

147
views

0
downloads

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, high dimensional space which is obtained by concatenating all the available features is reduced to a lower dimensional space by using the minimum redundancy maximum relevance feature selection method. ORL and UMIST face databases are used in experiments

Subject Keywords

Face recognition, Tellurium, Humans, Testing

URI

https://hdl.handle.net/11511/46065

DOI

https://doi.org/10.1109/siu.2006.1659818

Collections

Department of Computer Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

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...
Infrared face recognition Konuk, Uğur; Akar, Gözde; Department of Electrical and Electronics Engineering (2015) 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 performanc...
3D face recognition with local shape descriptors İnan, Tolga; Halıcı, Uğur; Department of Electrical and Electronics Engineering (2011) This thesis represents two approaches for three dimensional face recognition. In the first approach, a generic face model is fitted to human face. Local shape descriptors are located on the nodes of generic model mesh. Discriminative local shape descriptors on the nodes are selected and fed as input into the face recognition system. In the second approach, local shape descriptors which are uniformly distributed across the face are calculated. Among the calculated shape descriptors that are discriminative fo...
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 ...
Development of an algorithm for material selection Seyis, Önder; Atala, Haluk; Department of Metallurgical and Materials Engineering (2005) Material selection is one of the major points that should be taken into account seriously in the engineering design stage. Each material has various properties such as mechanical, thermal, electrical, physical, environmental, optical and biological properties. However, it is a well known fact that only a limited number of design engineers have a thorough knowledge on all these properties of a specific material, which is planned to be used in the manufacturing of the product. Therefore, the design engineer s...

Citation Formats

G. T. OZYER, E. Akbaş, and F. T. Yarman Vural, “A comparison of features spaces for face recognition problem,” 2006, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/46065.