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Broadcast News Story Segmentation Using Social Network Analysis and Hidden Markov Models

Publications associées (32)

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LOD Generation for Urban Scenes

Yannick Verdie

We introduce a novel approach that reconstructs 3D urban scenes in the form of levels of detail (LODs). Starting from raw data sets such as surface meshes generated by multi-view stereo systems, our algorithm proceeds in three main steps: classification, a ...

Association for Computing Machinery2015

Caenorhabditis elegant segmentation using texture-based models for motility phenotyping

Pascal Fua, Raphael Sznitman, Josué Sznitman

With widening interests in using model organisms for reverse genetic approaches and biomimmetic micro-robotics, motility phenotyping of the nematode Caenorhabditis elegans is expanding across a growing array of locomotive environments. One ongoing bottlene ...

Ieee-Inst Electrical Electronics Engineers Inc2014

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

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We propose an analysis of the social network composed of the characters appearing in Jean-Jacques Rousseau's autobiographic Les Confessions, with existence of edges based on co-occurrences. This work consists of twelve volumes, that span over fifty years o ...

2013

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Inference of Markov random field images segmentation models is usually performed using iterative methods which adapt the well-known expectation-maximization (EM) algorithm for independent mixture models. However, some of these adaptations are ad-hoc and ma ...

2011

This paper shows that Hidden Markov Models (HMMs) can be effectively ap- plied to 3D face data. The examined HMM techniques are shown to be superior to a previously examined Gaussian Mixture Model (GMM) technique. Experi- ments conducted on the Face Recogn ...

2010

Social Network Analysis in Multimedia Indexing: Making Sense of People in Multiparty Recordings

Sarah Favre

This paper presents an automatic approach to analyze the human interactions appearing in multiparty data, aiming at understanding the data content and at extracting social informa- tion such as Which role do people play?, What is their attitude?, or Can pe ...

2009

Automatic Role Recognition in Multiparty Recordings Using Social Networks and Probabilistic Sequential Models

Sarah Favre, Alessandro Vinciarelli

The automatic analysis of social interactions is attracting significant interest in the multimedia community. This work addresses one of the most important aspects of the problem, namely the recognition of roles in social exchanges. The proposed approach i ...

2009

Contextual classification of image patches with latent aspect models

Daniel Gatica-Perez, Jean-Marc Odobez, Florent Monay Michaud, Pedro Manuel Da Silva Quelhas

We present a novel approach for contextual classification of image patches in complex visual scenes, based on the use of histograms of quantized features and probabilistic aspect models. Our approach uses context in two ways: (1) by using the fact that spe ...

2009

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This paper presents experiments on the automatic recognition of roles in meetings. The proposed approach combines two sources of information: the lexical choices made by people playing different roles on one hand, and the Social Networks describing the int ...

2008