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Classical discriminant analysis attempts to discover a low-dimensional subspace where class label information is maximally preserved under projection. Canonical methods for estimating the subspace optimize an information-theoretic criterion that measures the separation between the class-conditional distributions. Unfortunately, direct optimization of the information-theoretic criteria is generally...
A robust, efficient video analytic tool is presented for detection and estimation of driver's head position and orientation in the SHRP 2 NDS dataset. It is shown that by exploiting the temporal correlations between successive frames in a video, challenging conditions such as lighting variations, and lower resolutions, may be mitigated effectively. The Viola-Jones frontal face detector provides initial...
This paper describes the architecture of a quadrotor and its linearized dynamic model. The attitude of the quadrotor in the model state-space variables can be calculated with rotational matrix formed from quaternions instead of finite small angular displacement approximation. Based on H∞ continuous time control method, a state feedback controller is designed to control the translational position and...
We describe a new online discriminative learning algorithm that efficiently and effectively recognizes phonemes in a speech sequence. The method builds upon recent work in online learning of a collection of generalized linear models using second order statistics of the model weight vectors. Evaluation on the TIMIT database shows that the algorithm achieves state-of-the-art phoneme recognition error...
A major hurdle of formal analysis of protocol security properties is the well-known state explosion - a protocol system usually contains infinitely many or a formidable number of states. As a result, most of the analysis resorts to heuristics, such as state space pruning. Given the temporal property of authentication and authorization protocols, we introduce trace inclusion transformation of protocol...
In this paper, we develop and validate a new Statistically Assisted Fluid Registration Algorithm (SAFIRA) for brain images. A non-statistical version of this algorithm was first implemented in and re-formulated using Lagrangian mechanics in. Here we extend this algorithm to 3D: given 3D brain images from a population, vector fields and their corresponding deformation matrices are computed in a first...
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