PhD Seminar Course on

An Introduction to Action Recognition and Tracking in Videos

Cagliari, April 12-20, 2011



This activity was made possible by the "Visiting Professors 2010" program of the University of Cagliari, sponsored by the Autonomous Region of Sardinia

Instructor: Prof. Massimo Piccardi
University of Bologna
Duration: 13 hours
Program:
  • Tuesday 12 April 2011 11:00-12:30; 14-15:30
    • Recalls of probability theory.
    • Main properties of the Gaussian distribution.
    • Gaussian mixture models.
  • Thursday 14 April 2011 11:00-12:30; 14-16:30
    • Concepts of Bayesian classification.
    • Density estimation.
    • Parametric and non-parametric estimators.
  • Monday 18 April 2011 11:00-12:30; 14-15:30
    • The hidden Markov model.
    • Action recognition.
  • Wednesday 20 April 2011 11:00-12:30; 14-16:30
    • Tracking in videos.
    • Recursive Bayesian estimation.
    • The Kalman filter.
    • Particle filters.
Venue:
Mezzanine room DIEE - Building A
Topics:

Objectives

This course will introduce the students to techniques for action recognition and tracking in videos. The first few lectures offer recalls of foundational topics such as probability, Bayesian classification and density estimation which will facilitate the comprehension of the following topics. Action classification covers the hidden Markov model, bag-of features approaches and conditional random fields. Tracking covers recursive Bayesian estimation and the Kalman and particle filters. The course aims to be of benefit for research students in the areas of computer vision, pattern recognition, multimedia, image and signal processing, human-computer interaction, and also computer science/computer engineering in general.

 

Learning modalities

The course will be taught over 4 days in eight slots, two slots per day with a break in between. The presentation will be based on slides and occasional use of whiteboard. The course can be taught in either Italian or English at the preference of the convenor.


Materials
All materials for the course will be in English. A copy of the slides will be provided to the students. The copyright of all materials stays with the copyright holders.

Topics at a glance

  • Recalls of probability theory
  • Concepts of Bayesian classification
  • Density estimation
  • The hidden Markov model 
  • Action recognition
  • Tracking in videos.
  • Recursive Bayesian estimation.
  • The Kalman filter.
  • Particle filters
Organizer: Prof. Fabio Roli
Dep. of Electrical and Electronic Engineering
University of Cagliari
Email: roli(at)diee(dot)unica(dot)it