Linguistic descriptors and fuzzy sets in face recognition realized by humans

In this study, we present a new approach to the face retrieval and face classification problem, which exploits available expert's knowledge and introduces a novel way of describing facial features. These features are described by manually assigned weights corresponding to membership grades with respect to the linguistic descriptors such as short, medium, or long. In the series of experiments, we also use weights produced by the Analytic Hierarchy Process aimed at producing saliences of facial cues. We identify a group of the most essential facial features.

[1]  Takehisa Onisawa,et al.  Interactive Face Generation from Verbal Description Using Conceptual Fuzzy Sets , 2008, J. Multim..

[2]  Xiaoou Tang,et al.  Surpassing Human-Level Face Verification Performance on LFW with GaussianFace , 2014, AAAI.

[3]  Lotfi A. Zadeh,et al.  Toward extended fuzzy logic - A first step , 2009, Fuzzy Sets Syst..

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

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

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

[7]  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).

[8]  Witold Pedrycz,et al.  An Introduction to Fuzzy Sets , 1998 .

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

[10]  Ming Yang,et al.  DeepFace: Closing the Gap to Human-Level Performance in Face Verification , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[11]  P. N. Bellhumer.  Eigenfaces vs. fisherfaces : Recognition using class specific linear projection , 1997 .

[12]  Ekta Vats,et al.  Fuzzy human motion analysis: A review , 2014, Pattern Recognit..

[13]  Anca L. Ralescu,et al.  Towards a multimedia model-based image retrieval system using fuzzy logic , 1993 .

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

[15]  Toshio Norita.  Fuzzy Theory in an Image Understanding Retrieval System , 1994 .

[16]  James M. Keller,et al.  Linguistic description of adult skeletal age-at-death estimations from fuzzy integral acquired fuzzy sets , 2011, 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011).

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

[18]  Ozy Sjahputera,et al.  Linguistic description of relative positions in images , 2001, IEEE Trans. Syst. Man Cybern. Part B.

[19]  Harry Wechsler,et al.  The FERET database and evaluation procedure for face-recognition algorithms , 1998, Image Vis. Comput..

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

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

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

[23]  Xiaogang Wang,et al.  Deep Learning Face Representation from Predicting 10,000 Classes , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[24]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[25]  Allen Y. Yang,et al.  Robust Face Recognition via Sparse Representation , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[26]  Takehisa Onisawa,et al.  Drawing human faces using words and conceptual fuzzy sets , 2007, 2007 IEEE International Conference on Systems, Man and Cybernetics.

[27]  Ammad Ali,et al.  Face Recognition with Local Binary Patterns , 2012 .