Cognitive and computational aspects of gender estimation from faces

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Date

2002

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Balcı, M. Koray

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The aim of this work is to propose a computationally feasible and cognitively plausible model for face processing, and to develop a system for gender estima tion from face images. For this purpose, we propose a general face processing model that encapsulates all face-specific tasks. The model is inspired by the find ings from cognitive studies. We implement the core of the whole model which uses Principal Component Analysis (PCA) procedure and develop a classifier for gender estimation. As classifier, we implement a Multi Layer Perceptron (MLP). MLP is further pruned for observing the minimal input set necessary for the mtask. By our priming approach we end up with a robust and efficient classifier. We confirm the importance of higher-eigenvalued eigenvectors and also show that only a small subset of them are sufficient for gender estimation. We test our ap proach in two different face databases, one of which is the largest face database publicly available today and widely used in recent studies. Until this study, PCA approach for gender estimation has not been tested on a large database such as this one.

Subject Keywords

Face processing, Gender estimation, Principal Component Analysis (PCA), Multi Layer Perceptrons (MLP)

URI

https://hdl.handle.net/11511/12179

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Graduate School of Informatics, Thesis

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Citation Formats

M. K. Balcı, “Cognitive and computational aspects of gender estimation from faces,” Middle East Technical University, 2002.