Concept

Markov information source

Related publications (32)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

HMM-Based Error Correction Mechanism for Five-Key Chording Keyboards

Pierre Dillenbourg, Bixio Rimoldi, Adrian Dan Tarniceriu

As different text input devices lead to different typing error patterns, considering the device characteristics when designing an error correction mechanism can lead to significantly improved results. In this paper, we propose and evaluate a spelling corre ...

2015

Duration models for activity recognition and prediction in buildings using Hidden Markov Models

Jean Hennebert, Nikolaos Zarkadis

Activity recognition and prediction in buildings can have multiple positive effects in buildings: improve elderly monitoring, detect intrusions, maximize energy savings and optimize occupant comfort. In this paper we apply human activity recognition by usi ...

IEEE2015

Single-Handed Eyes-Free Universal Input Device

Adrian Dan Tarniceriu

For most people, interacting with a mobile device requires visual commitment to the input mechanism. As a consequence, there are many situations in our daily life when we have to refrain from using these devices, as our vision is already committed: for ins ...

EPFL2015

Statistical models for HMM/ANN hybrids

Philip Neil Garner, David Imseng

We present a theoretical investigation into the use of normalised artificial neural network (ANN) outputs in the context of hidden Markov models (HMMs). The work is motivated by the pursuit of a more theoretically rigorous understanding of the Kullback-Lie ...

Idiap2013

A novel statistical generative model dedicated to face recognition

Sébastien Marcel, Guillaume Heusch

In this paper, a novel statistical generative model to describe a face is presented, and is applied to the face authentication task. Classical generative models used so far in face recognition, such as Gaussian Mixture Models (GMMs) and Hidden Markov Model ...

2010

Pedestrian localization, tracking and behavior analysis from multiple cameras

Jérôme Berclaz

Video surveillance is currently undergoing a rapid growth. However, while thousands of cameras are being installed in public places all over the world, computer programs that could reliably detect and track people in order to analyze their behavior are not ...

EPFL2010

Modeling of distortion caused by Markov-model burst packet losses in video transmission

Yi Zhang

This paper addresses the problem of distortion modeling for video transmission over burst-loss channels characterized by a finite state Markov chain. A Distortion Trellis model is pro- posed, enabling us to estimate at the frame level the expected mean-squ ...

2009

Sliding Window Abstraction for Infinite Markov Chains

Maria-Emanuela-Canini Mateescu, Verena Wolf

We present ail on-the-fly abstraction technique for infinite-state continuous-time Markov chains. We consider Markov chains that are specified by a finite set of transition classes. Such models naturally represent biochemical reactions and therefore play a ...

Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa2009

Sliding Window Abstraction for Infinite Markov Chains

Maria-Emanuela-Canini Mateescu, Verena Wolf

We present an on-the-fly abstraction technique for infinite-state continuous-time Markov chains. We consider Markov chains that are specified by a finite set of transition classes. Such models naturally represent biochemical reactions and therefore play an ...

2009

Trajectory analysis using point distribution models

Pierre Roduit

This thesis focuses on the analysis of the trajectories of a mobile agent. It presents different techniques to acquire a quantitative measure of the difference between two trajectories or two trajectory datasets. A novel approach is presented here, based o ...

EPFL2009