Alex I. Bazin

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This paper describes the development of a prototype floor sensor as a gait recognition system. This could eventually find deployment as a standalone system (eg. a burglar alarm system) or as part of a multimodal biometric system. The new sensor consists of 1536 individual sensors arranged in a 3 m by 0.5 m rectangular strip with an individual sensor area of(More)
A common requirement in speech technology is to align two different symbolic representations of the same linguistic ‘message’. For instance, we often need to align letters of words listed in a dictionary with the corresponding phonemes specifying their pronunciation. As dictionaries become ever bigger, manual alignment becomes less and less tenable yet(More)
In this paper we describe a novel method for gait based identity verification based on Bayesian classification. The verification task is reduced to a two class problem (Client or Impostor) with logistic functions constructed to provide probability estimates of intra-class (Client) and inter-class (Impostor) likelihoods. These likelihoods are combined using(More)
The development of large scale biometric systems requires experiments to be performed on large amounts of data. Existing capture systems are designed for fixed experiments and are not easily scalable. In this scenario even the addition of extra data is difficult. We developed a prototype biometric tunnel for the capture of non-contact biometrics. It is self(More)
Current biometric capture methodologies were born in a laboratory environment. In this scenario you have cooperative subjects, large time capture windows, and staff to edit and mark up data as necessary. However, as biometrics moves from the laboratory these factors impinge upon the scalability of the system. In this work we developed a prototype biometric(More)
This paper describes a novel probabilistic framework for biometric identification and data fusion. Based on intra and inter-class variation extracted from training data, posterior probabilities describing the similarity between two feature vectors may be directly calculated from the data using the logistic function and Bayes rule. Using a large publicly(More)
This paper examines the fusion of various gait metrics in a probabilistic framework. Using three gait modalities we describe a process for determining probabilistic match scores using intra and inter-class variance models together with Bayes rule. We then propose to fuse these modalities based on established fusion rules with weights determined in a(More)