Age Invariant Face Recognition

Abstract

The Brain-Like Artificial Intelligence (BLAI) is pioneered by Prof.Nikola Kasabov and here it is applied to a specific application.

In this project we develop methods and systems for two inter-related problems in face recognition using the Neucube neuromorphic computational platform. The two systems developed are for: (1) age classification; (2)  and gender recognition.

The well-known FG-NET and MORPH Album 2 image gallery were used and anthropometric features were extracted from landmark points on the face. The landmarks were first pre-processed with the procrustes algorithm before feature extraction was performed. The Weka machine learning workbench was used to compare the performance of traditional techniques such as the K nearest neighbor (Knn) and Multi-LayerPerceptron (MLP) with NeuCube. Our empirical results show that NeuCube performed consistently better across both problem types that we investigated

Figure: Schematic representation of the NeuCube-based methodology for mapping, learning, visualisation and classification.

Related Papers and Benchmarking

The proposed methods and systems, when compared with traditional statistical and machine learning methods, showed superior results in the following aspects:

  1. Better data analysis and classification/regression accuracy (by 10 to 40%);
  2. Better visualisation of the created models, with a possible use of VR;
  3. Better understanding of the data and the processes that are measured;
  4. Enabling new information and knowledge discovery through meaningful interpretation of the models.

See also some of the related papers:

Alvi, F. B., & Pears, R. (2017). A composite spatio-temporal modeling approach for age invariant face recognition. Expert Systems with Applications, 72, 383-394.

Alvi, F. B., Pears, R., & Kasabov, N. (2017). An evolving spatio-temporal approach for gender and age group classification with Spiking Neural Networks. Evolving Systems, 1-12.


R&D System

For this project, an R&D system has been developed based on NeuCube. The system can be obtained subject to licensing agreement.


Developer

The developer of this project is:

Fahad Alvi