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This article provides an overview of the basic research directions in the field of gait analysis and recognition. The recent developments in gait research indicate that gait technologies still need to mature and that limited practical applications should be expected in the immediate future. At present, there is a potential for initial deployment of gait for(More)
—A new class of filters for multichannel image processing is introduced and analyzed in this brief. This class constitutes a generalization of vector directional filters. The proposed filters use fuzzy transformations of the angles among the different vectors to adapt to local data in the image. The principle behind the new filters is explained and(More)
Changeability, privacy protection, and verification accuracy are important factors for widespread deployment of biometrics based au-thentication systems. In this paper, we introduce a method for effective combination of biometrics data with user specific secret key for human verification. The proposed approach is based on discretized random orthonormal(More)
Face recognition has been employed in various security-related applications such as surveillance, mugshot identification, e-passport, and access control. Despite its recent advancements, privacy concern is one of several issues preventing its wider deployment. In this paper, we address the privacy concern for a self-exclusion scenario of face recognition,(More)
This paper presents a method for changeable cryptographic key generation using face biometrics signal. A previously introduced scheme, fuzzy vault, is utilized for secure binding of randomly generated key with extracted biometrics features. The major technical difficulty is to map noisy biometrics representation to the exactly correct key. In this paper,(More)
Biometric signals are mostly multidimensional objects, known as tensors. Recently, there has been a growing interest in multilinear discriminant analysis (MLDA) solutions operating directly on these tensorial data. However, the relationships among these algorithms and their connections to linear (vector-based) algorithms are not clear, and in-depth(More)
In this paper, we present a boosted linear discriminant analysis (LDA) solution with regularization on features extracted by the multilinear principal component analysis (MPCA) for the gait recognition problem. This work is an extension of a recent LDA-based boosting approach and the MPCA is employed to project tensorial gait samples on a number of(More)
This paper proposes a novel uncorrelated multilinear dis-criminant analysis (UMLDA) algorithm for the challenging problem of gait recognition. A tensor-to-vector projection (TVP) of tensor objects is formulated and the UMLDA is developed using TVP to extract uncorrelated discriminative features directly from tensorial data. The small-sample-size (SSS)(More)