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In this paper, we propose a hierarchical state-based model for representing an echocardiogram video. It captures the semantics of video segments from dynamic characteristics of objects present in each segment. Our objective is to provide an effective method for segmenting an echo video into view, state, and substate levels. This is motivated by the need for(More)
This paper explores options to the built-in authentication mechanism of the Google Glass which is vulnerable to shoulder surfing attacks. Two simple PIN-based authentication techniques are presented, both of which provide protection against shoulder surfing. The techniques employ two interfaces for entering the PIN, namely, voice (Voice-based PIN) and(More)
Monitoring neonatal EEG signal is useful in identifying neonatal convulsions or seizures. For neonates, seizures can be electrographic, electro clinical, or both simultaneously. Electrographic seizure is identified via recorded EEG signal, while electro clinical seizures exhibit clinical manifestations. Sometimes neonates can exhibit silent seizures which(More)
This paper investigates the security of partial fingerprint-based authentication systems, especially when multiple fingerprints of a user are enrolled. A number of consumer electronic devices, such as smartphones, are beginning to incorporate fingerprint sensors for user authentication. The sensors embedded in these devices are generally small and the(More)
This paper proposes a method for the identification of individuals from their gait using fuzzy logic. Gait signature is first extracted in the form of a spatiotemporal representation called Gait Energy Image (GEI). Since the dimension of GEI is very high, we use fuzzy principal component analysis (FPCA) for dimension reduction. Unlike traditional PCA, it(More)
In this paper we evaluate the accuracy of warping of neuro-images using brain deformation predicted by means of a patient-specific biomechanical model against registration using a BSpline-based free form deformation algorithm. Unlike the BSpline algorithm, biomechanics-based registration does not require an intra-operative MR image which is very expensive(More)
This paper studies continuous authentication for touch interface based mobile devices. A Hidden Markov Model (HMM) based behavioral template training approach is presented, which does not require training data from other subjects other than the owner of the mobile. The stroke patterns of a user are modeled using a continuous left-right HMM. The approach(More)