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In this paper, a solution to the problem of Active Authentication using trace histories is addressed. Specifically, the task is to perform user verification on mobile devices using historical location traces of the user as a function of time. Considering the movement of a human as a Markovian motion, a modified Hidden Markov Model (HMM)-based solution is proposed. The proposed method, namely the Marginally...
We propose multi-task, multivariate low-rank representation-based methods for multimodal biometrics recognition. Our methods can be viewed as a generalized version of multivariate low-rank regression, where low-rank representation across all the modalities is imposed. One of our methods takes into account coupling information among different biometric modalities simultaneously by enforcing the common...
Screen touch gesture has been shown to be a promising modality for touch-based active authentication of users of mobile devices. In this paper, we present an approach for active user authentication using screen touch gestures by building linear and kernelized dictionaries based on sparse representations and associated classifiers. Experiments using a new dataset collected by us as well as two other...
We address the problem of recognizing offensive play strategies from American football play videos. Specifically, we propose a probabilistic model which describes the generative process of an observed football play and takes into account practical issues in real football videos, such as difficulty in identifying offensive players, view changes, and tracking errors. In particular, we exploit the geometric...
Understanding activities arising out of the interactions of a configuration of moving objects is an important problem in video understanding, with applications in surveillance and monitoring. A special situation is when the objects are small enough to be represented as points on a 2D plane. In this paper, we introduce a novel method of representing the activity by the deformations of the point configuration...
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