Publication

Combining SVMs for Face Class Modeling

Jean-Philippe Thiran, Vlad Popovici
2005
Conference Papers

Abstract

We present a method for combining a number of Support Vector Machines trained independently in the eigenface space and we apply it to face class modeling. We first train several

Official source

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Jean-Philippe Thiran, Vlad Popovici
2005
Conference Papers

Abstract

We present a method for combining a number of Support Vector Machines trained independently in the eigenface space and we apply it to face class modeling. We first train several

Official source

Related concepts (14)

Eigenface

An eigenface (ˈaɪgənˌfeɪs) is the name given to a set of eigenvectors when used in the computer vision problem of human face recognition. The approach of using eigenfaces for recognition was developed by Sirovich and Kirby and used by Matthew Turk and Alex Pentland in face classification. The eigenvectors are derived from the covariance matrix of the probability distribution over the high-dimensional vector space of face images. The eigenfaces themselves form a basis set of all images used to construct the covariance matrix.

Supervised learning

Supervised learning (SL) is a paradigm in machine learning where input objects (for example, a vector of predictor variables) and a desired output value (also known as human-labeled supervisory signal) train a model. The training data is processed, building a function that maps new data on expected output values. An optimal scenario will allow for the algorithm to correctly determine output values for unseen instances. This requires the learning algorithm to generalize from the training data to unseen situations in a "reasonable" way (see inductive bias).

Facial recognition system

A facial recognition system is a technology potentially capable of matching a human face from a or a video frame against a database of faces. Such a system is typically employed to authenticate users through ID verification services, and works by pinpointing and measuring facial features from a given image. Development began on similar systems in the 1960s, beginning as a form of computer application. Since their inception, facial recognition systems have seen wider uses in recent times on smartphones and in other forms of technology, such as robotics.

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Combining SVMs for Face Class Modeling

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