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Model-based approaches to Speaker Verification (SV), such as Joint Factor Analysis (JFA), i-vector and relevance Maximum-a-Posteriori (MAP), have shown to provide state-of-the-art performance for text-dependent systems with fixed phrases. The performance of i-vector and JFA models has been further enhanced by estimating posteriors from Deep Neural Network (DNN) instead of Gaussian Mixture Model (GMM)...
Initialization and feature selection are crucial in supervised landmark detection. Mismatching caused by detector error and discrepant initialization is very common in these existing methods. To solve this problem, we proposed a new method, which includes a new initialize model and multitask feature learning, for the robust facial landmark localization. In our new method, firstly, a fast detection...
Visual-based 3D model retrieval presents great potential, for its broad application prospects and relatively high accuracy. A branch of visual-based methods utilizes scale invariant feature transform (SIFT) on 2D rendered images of a 3D model viewed from regularly sampled locations on a sphere, and then the bag-of-words framework is employed to improve the retrieval precision. However, in existing...
Cardiopulmonary resuscitation (CPR) artifact filtering techniques have not been successfully combined with commercial shock advice algorithms (SAA) to diagnose the rhythm during CPR. Recently, a promising new approach based on using SAAs especially designed to diagnose the filtered ECG has been introduced. This study evaluates the impact of filtering CPR artifacts on the shock/noshock decision for...
This paper presents a new similarity measure and matching scheme for content-based image retrieval (CBIR), based on modeling positive and negative hypotheses and testing a query image against these two hypotheses. The paper proposes to calculate first a universal image model (UIM), which is built based on a large set of images. The derived UIM is then used as a reference for the calculation of adapted...
In this paper, we present an approach for person re-identification in multi-camera networks. This approach employs the Implicit Shape Model and SIFT features for person re-identification. One important property of the re-identification approach is that it is closely coupled to a person detection and tracking and uses SIFT feature models which are built during the tracking. We hold this coupling to...
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