On Some Aspects of an Aggregation Mechanism in Face Recognition Problems

In the paper, we investigate the problem of an aggregation of classifiers based on numerical and linguistic values of facial features. In the literature, there are many reports of the studies discussing the aggregation or information fusion, however in the situation when the specific classification methods utilize numeric, not linguistic values. Here, we examine the well-known methods (Eigenfaces, Fisherfaces, LBP, MB-LBP, CCBLD) supported by the linguistic values of the measurable facial segments. The detailed results of experiments on the MUCT and PUT facial databases show which of the common aggregation functions and methods have a significant potential to improve the classification process.

[1]  R. Mesiar,et al.  ”Aggregation Functions”, Cambridge University Press , 2008, 2008 6th International Symposium on Intelligent Systems and Informatics.

[2]  Witold Pedrycz,et al.  Development of Multimodal Biometric Systems with Three-Way and Fuzzy Set-Based Decision Mechanisms , 2017, International Journal of Fuzzy Systems.

[3]  Rafal Grycuk,et al.  Content-Based Image Indexing by Data Clustering and Inverse Document Frequency , 2014, BDAS.

[4]  Hong Yan,et al.  Human Face Image Recognition: An Evidence Aggregation Approach , 1998, Comput. Vis. Image Underst..

[5]  Anca L. Ralescu,et al.  Improved retrieval in a fuzzy database from adjusted user input , 1995, Journal of Intelligent Information Systems.

[6]  Shengcai Liao,et al.  Learning Multi-scale Block Local Binary Patterns for Face Recognition , 2007, ICB.

[7]  Chengjun Liu,et al.  Fusion of color, local spatial and global frequency information for face recognition , 2010, Pattern Recognit..

[8]  David J. Kriegman,et al.  Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection , 1996, ECCV.

[9]  J. Bezdek,et al.  FCM: The fuzzy c-means clustering algorithm , 1984 .

[10]  Soraia Raupp Musse,et al.  Eyes and Eyebrows Detection for Performance Driven Animation , 2010, 2010 23rd SIBGRAPI Conference on Graphics, Patterns and Images.

[11]  Majid Ahmadi,et al.  N-feature neural network human face recognition , 2004, Image Vis. Comput..

[12]  M. Turk,et al.  Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.

[13]  Oscar Castillo,et al.  Face recognition using modular neural networks and fuzzy Sugeno integral for response integration , 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

[14]  Witold Pedrycz,et al.  Springer Handbook of Computational Intelligence , 2015, Springer Handbook of Computational Intelligence.

[15]  Gaspar Mayor,et al.  Aggregation Operators , 2002 .

[16]  Witold Pedrycz,et al.  Utility functions as aggregation functions in face recognition , 2016, 2016 IEEE Symposium Series on Computational Intelligence (SSCI).

[17]  Oscar Castillo,et al.  Face Recognition with Choquet Integral in Modular Neural Networks , 2014, Recent Advances on Hybrid Approaches for Designing Intelligent Systems.

[18]  Chi-Ho Chan.  Multi-scale local Binary Pattern Histogram for Face Recognition , 2007, ICB.

[19]  M. M. Sufyan Beg,et al.  Face sketch recognition using sketching with words , 2015, Int. J. Mach. Learn. Cybern..

[20]  Gleb Beliakov,et al.  Aggregation Functions: A Guide for Practitioners , 2007, Studies in Fuzziness and Soft Computing.

[21]  Witold Pedrycz,et al.  Granular Computing: Analysis and Design of Intelligent Systems , 2013 .

[22]  Oscar Castillo,et al.  Face Recognition with a Sobel Edge Detector and the Choquet Integral as Integration Method in a Modular Neural Networks , 2015, Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization.

[23]  Witold Pedrycz,et al.  An Evaluation of Fuzzy Measure for Face Recognition , 2017, ICAISC.

[24]  Matti Pietikäinen,et al.  Face Recognition with Local Binary Patterns , 2004, ECCV.

[25]  Alex Pentland,et al.  View-based and modular eigenspaces for face recognition , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[26]  Rafal Grycuk,et al.  Content-based image retrieval optimization by differential evolution , 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

[27]  Witold Pedrycz,et al.  On developing Sugeno fuzzy measure densities in problems of face recognition , 2017 .

[28]  Witold Pedrycz,et al.  Linguistic descriptors in face recognition: A literature survey and the perspectives of future development , 2015, 2015 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA).

[29]  Witold Pedrycz,et al.  A study in facial regions saliency: a fuzzy measure approach , 2014, Soft Comput..

[30]  Rafal Grycuk,et al.  From Single Image to List of Objects Based on Edge and Blob Detection , 2014, ICAISC.

[31]  Witold Pedrycz,et al.  Chain Code-Based Local Descriptor for Face Recognition , 2015, CORES.

[32]  Witold Pedrycz,et al.  Generalized Choquet Integral for Face Recognition , 2018, Int. J. Fuzzy Syst..

[33]  Witold Pedrycz,et al.  Face recognition using fuzzy Integral and wavelet decomposition method , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[34]  Witold Pedrycz,et al.  An application of chain code-based local descriptor and its extension to face recognition , 2017, Pattern Recognit..

[35]  Adam Schmidt,et al.  The put face database , 2008 .

[36]  Roberto Brunelli,et al.  Face Recognition: Features Versus Templates , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[37]  Witold Pedrycz,et al.  A study in facial features saliency in face recognition: an analytic hierarchy process approach , 2016, Soft Computing.

[38]  Elisabeth Rakus-Andersson,et al.  Face Classification Based on Linguistic Description of Facial Features , 2014, ICAISC.

[39]  Witold Pedrycz,et al.  Aggregation of classifiers based on image transformations in biometric face recognition , 2008, Machine Vision and Applications.

[40]  Shree K. Nayar,et al.  Ieee Transactions on Pattern Analysis and Machine Intelligence Describable Visual Attributes for Face Verification and Image Search , 2022 .

[41]  Shree K. Nayar,et al.  Attribute and simile classifiers for face verification , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[42]  Witold Pedrycz,et al.  Face recognition: A study in information fusion using fuzzy integral , 2005, Pattern Recognit. Lett..

[43]  Witold Pedrycz,et al.  Comparative analysis of logic operators: A perspective of statistical testing and granular computing , 2015, Int. J. Approx. Reason..