All students must validate 30 ECTS per semester.We offer two speciality tracks:

Track 1: Vision and Applications
The first track focuses on various applications of computer vision: biomedical applications, people detection, object tracking, computational photography.

Track 2: Vision and devices
The second track focuses on devices to capture images (intelligent sensors, medical imaging systems) and to visualise and interact with them (augmented reality)

 

 

 

Course name: Applied Video Sequences Analysis Credits: 6

  • Class type: Theory+Practice
  • Hours per week: 2+1
  • Type of the exam: 75% Lab assigments, 25% theory exam

Content

The aim of this course is to train the student in the practical use of basic and state-of-the-art algorithms for the analysis of a video sequence. This course will be project-oriented, focused on handling these algorithms with the help of the OpenCV software library.

UNIT I: Foreground/Objects detection and segmentation

  • Background subtraction: parametric and  non-parametric models
  • Shadow detection
  • Specific object detectors

UNIT II: Video object tracking

  • Template matching
  • Mean-shift tracking
  • Kalman and Particle Filters
  • Tracking by detection

UNIT III: Event detection and understanding

  • Definitions
  • Sparse scenarios
  • Crowded scenarios

 

Recommended reading

  • T. Moeslund, Introduction to video and image processing: Building real systems and applications. Springer Science & Business Media, 2012.
  • T. Bouwmans, F. Porikli, B. Hferlin, and A. Vacavant. Background Modeling and Foreground Detection for Video Surveillance. Chapman and Hall/CRC, 2014
  • E. Maggio, A. Cavallaro, Video Tracking: Theory and Practice, Wiley, 2011.
  • Fu, Yun, ed. Human Activity Recognition and Prediction. Springer, 2015.
  • Atrey, M. Kankanhalli, and A. Cavallaro, eds. Intelligent multimedia surveillance: current trends and research. Springer Science & Business Media, 2013.
  • A. Kaehler and G. Bradski. Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library. O'Reilly Media, Inc., 2016.
  • Lecturer (name, position, degree): Juan Carlos San Miguel, Ph.D., Associate Professor
  • Additional lecturers, if exist(name, position, degree): Marcos Escudero-Vinolo, Ph.D., Associate Professor ; José M. Martínez, Ph.D., Full Professor

The European Credit Transfer and Accumulation System (ECTS) is a student-centred system based on the student workload required to achieve the objectives of a programme of study. Its aim is to facilitate the recognition of study periods undertaken abroad by mobile students through the transfer credits. The ECTS is based on the principle that 60 credits are equivalent to the workload of full-time student during one academic year.