Authors:
Ladislav Lenc
and
Pavel Král
Affiliation:
University of West Bohemia, Czech Republic
Keyword(s):
Automatic Face Recognition, Czech News Agency, Confidence Measures, Gabor Wavelets, Scale Invariant Feature Transform.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computational Intelligence
;
Data Manipulation
;
Evolutionary Computing
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Machine Learning
;
Methodologies and Methods
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Soft Computing
;
Symbolic Systems
;
Vision and Perception
Abstract:
This paper deals with Automatic Face Recognition (AFR). The main contribution of this work consists in the evaluation of our two previously proposed AFR methods in real conditions. At first, we compare and evaluate the recognition accuracy of two AFR methods on well-controlled face database. Then we compare these results with the recognition accuracy on a real-world database of comparable size. For such comparison,
we use a sub-set of the newly created Czech News Agency (ˇCTK) database. This database is created from the real photos acquired by the ˇCTK and the creation of this corpus represents the second contribution of this work. The experiments show the significant differences in the results on the controlled and real-world data. 100% accuracy is achieved on the ORL database while only 72.7% is the best score for the ˇCTK database. Further experiments show, how the recognition rate is influenced by the number of training images for each person and by the size of the database. We a
lso demonstrate, that the recognition rate decreases significantly with larger database. We propose a confidence measure technique as a solution to identify and to filter-out the incorrectly recognized faces. We further show that confidence measure is very beneficial for AFR under real conditions.
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