EE-623 / 4 crédits

Enseignant: Odobez Jean-Marc

Langue: Anglais

Remark: Next time: Fall 2024


Frequency

Every 2 years

Summary

The course will cover different aspects of multimodal processing (complementarity vs redundancy; alignment and synchrony; fusion), with an emphasis on the analysis of people, behaviors and interactions from multimodal sensor, using statistical models and deep learning as main modeling tools.

Content

Keywords

Multimodality, human activity analysis, interactions, machine learning, computer vision, audio processing.

Learning Prerequisites

Required courses

Undergraduate-level knowledge of linear algebra, statistics, image and signal processing.

Recommended courses

Introduction to machine learning course.

Assessment methods

Written and oral.

Resources

Bibliography

Pattern Recognition and Machine Learning, C·. Bishop, Springer, 2008.

 

Ressources en bibliothèque

Dans les plans d'études

  • Nombre de places: 20
  • Forme de l'examen: Ecrit & Oral (session libre)
  • Matière examinée: Perception and learning from multimodal sensors
  • Cours: 28 Heure(s)
  • Exercices: 10 Heure(s)
  • TP: 18 Heure(s)

Semaine de référence

Cours connexes

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