Exploring Contextual Information in a Layered Framework for Group Action Recognition
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State-of-the-art automatic speech recognition (ASR) techniques are typically based on hidden Markov models (HMMs) for the modeling of temporal sequences of feature vectors extracted from the speech signal. At the level of each HMM state, Gaussian mixture m ...
State-of-the-art automatic speech recognition (ASR) techniques are typically based on hidden Markov models (HMMs) for the modeling of temporal sequences of feature vectors extracted from the speech signal. At the level of each HMM state, Gaussian mixture m ...
Lab sessions given in relation to Herve Bourlard's Speech Recognition course at EPFL (Ecole Polytechnique Federale de Lausanne), second semester 2001. The full session is available from the web as ftp://ftp.idiap.ch/pub/sacha/labs/Session2.tgz . ...
We propose a deep study on tissue modelization and classification Techniques on T1-weighted MR images. Three approaches have been taken into account to perform this validation study. Two of them are based on Finite Gaussian Mixture (FGM) model. The first o ...
This paper proposes the use of Gaussian Mixture Models to estimate conditional probability density functions. A conditional Gaussian Mixture Model has been compared to the geostatistical method of Sequential Gaussian Simulations. The data set used is a par ...
In this paper we propose a method to segment and recognize text embedded in video and images. We modelize the gray level distribution in the text images as mixture of gaussians, and then assign each pixel to one of the gaussian layer. The assignment is bas ...
We study the rationality of learning and the biases in expectations in the Iowa Experimental Markets. Using novel tests developed in (Bossaerts, P., 1996. Martingale restrictions on equilibrium security prices under rational expectations and consistent bel ...
A method for segmenting and recognizing text embedded in video and images is proposed in this paper. In the method, multiple segmentation hypotheses of text image are first generated based on a MRF model. Background regions in each hypothesis are then remo ...
In this paper we propose a method to segment and recognize text embedded in video and images. We modelize the gray level distribution in the text images as mixture of gaussians, and then assign each pixel to one of the gaussian layer. The assignment is bas ...
A method for segmenting and recognizing text embedded in video and images is proposed in this paper. In the method, multiple segmentation hypotheses of text image are first generated based on a MRF model. Background regions in each hypothesis are then remo ...
