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Brain inspired face recognition: A computational framework.

Authors :
Roy Chowdhury, Pinaki
Singh Wadhwa, Angad
Tyagi, Nikhil
Source :
Cognitive Systems Research. Mar2023, Vol. 78, p1-13. 13p.
Publication Year :
2023

Abstract

This paper presents a new proposal of an efficient computational model of face recognition which uses cues from the distributed face recognition mechanism of the brain, and by gathering engineering equivalent of these cues from existing literature. Three distinct and widely used features – Histogram of Oriented Gradients (HOG), Local Binary Patterns (LBP), and Principal components (PCs) extracted from target images are used in a manner which is simple, and yet effective. The HOG and LBP features further undergo Principal Component Analysis (PCA) for dimensionality reduction. Our model uses multi-layer perceptrons (MLP) to classify these three features and fuse them to form a sparsely connected model. A computational theory is first developed by using concepts from the information processing mechanism of the brain. Extensive experiments are carried out using eight publicly available face datasets to validate our proposed model's performance in recognizing faces with extreme variation of illumination, pose angle, expression, and background. We also investigate the same mechanism because of reasons discussed later, on object recognition tasks as well. Results obtained are extremely promising when compared with other face and object recognition algorithms including CNN and deep learning-based methods. This highlights that simple computational processes, if clubbed properly, can produce competing performance with best algorithms. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13890417
Volume :
78
Database :
Academic Search Index
Journal :
Cognitive Systems Research
Publication Type :
Academic Journal
Accession number :
161344210
Full Text :
https://doi.org/10.1016/j.cogsys.2022.11.006