Room and Time

Lecture: 13/305, Monday, 08:00-09:30
Exercise: 32-411-PC, Wednesday, 14:15-15:45, see below

Contacts

Prof. Dr. Didier Stricker 
Dr. Gabriele Bleser: Gabriele.Bleser(at)dfki.de 

Topics:

• Edge, corner and blob detection
• Feature descriptors and matching
• Background modelling and subtraction
• Feature tracking and optical flow
• Object detection
• Recursive Bayesian tracking
• (Extended) Kalman filter and particle filter
• Applications

Slides

The slides will be continuously added here:

• 28.04.2014: Introduction
• 05.05.2014: Edge and corner detection
• 12.05.2014: Blobs & Scale Invariance
• 19.05.2014: Descriptors
• 26.05.2014: Background subtraction
• 02.06.2014: Optical flow
• 16.06.2014: Bayesian tracking framework
• 23.06.2014: Kalman filter
• 30.06.2014: Extended Kalman filter
• 07.07.2014: Particle filter
• 14.07.2014: Visual Object Tracking
• 21.07.2014: Visual Object Tracking 2

Exercises

Please read the exercise policy (updated at 13.05.2014). Assignments will appear here:

• Matlab Introduction (As supplementary material, no submission)
• Exercise Sheet 1 (Deadline: 20.05., exercise session on 21.05.)
• Exercise Sheet 2 (Deadline: 02.06., exercise session on 04.06.)
• Exercise Sheet 3 (Deadline: 30.06., on 02.07. at DFKI, room 1.04)
• Exercise Sheet 4 (Deadline: 21.07., exercise session on 13.08. at DFKI, room 1.04)

Bibliography (textbooks)

• David A. Forsyth and Jean Ponce, Computer Vision: A Modern Approach
• Richard Hartley and Andrew Zisserman, Multiple View Geometry in Computer Vision
• Y. Ma, S. Soatto, J. Kosecka, S. Sastry, An invitation to 3D Vision, 2003
• Giorgio Panin, Model-based visual tracking, ed. Wiley-Blackwell
• Sebastian Thrun, Probabilistic Robotics (http://www.probabilistic-robotics.org/)
• Y. Bar-Shalom, Estimation with Applications to Tracking and Navigation: Theory Algorthims and Software: Theory Algorithms and Software