F034606: Visual Computing Theory and Engineering

Table of Contents

Welcome all of you to the class of Visual Computing Theory and Engineering 2017 !

Course

Class Time and Location:

  • Lectures: Tuesday, 18:00-20:20, Room 1-200, DongZhongYuan Building(东中院)
  • Course Teaching Assistant: Minsi Wang (wang_minsi@163.com)
  • TA Office: Room 321, IEEE Building #5

Course Description

The audiences of this elective class are graduated students in School of Electronic Information and Electrical Engineering, featured by practical engineering works. The main contents include visual models, image texture analysis and synthesis, motion analysis, multiview geometry, machine learning in computer vision, visual computing theory, etc. It is intended to be a broadly accessible course about visual computation related application, such as gist extraction, image structure extraction, photo inpainting, color video or image carton, video stabilization, image stitching, multi-objects tracking, color image stereo matching, structure from motion, object recognition from video surveillance and abnormal events detection, etc.

(Credits/Credit Hours):2/36,11 weeks

Grading Policy

  • Show up and discuss in class: 30%
  • Reading report : 30%
  • Review/Project paper: 40%

Your project paperwill be graded based on 3 major components:

  • Clarity of write-up and presentation (for open project)
  • Technical soundness and innovation
  • Results and Evaluation

HW and Project Submission:

  • All assignments should be finished before deadline.

Prerequisites

  • Basic Knowledge of Image Processing
  • C/Matlab Programming experiences

Textbook

No required textbooks; Suggested textbooks:

  1. R. Szeliski, “Computer Vision: Algorithms and Applications”, Springer, 2010.
  2. S. Prince, “Computer vision: models, learning and inference”, Cambridge University Press, 2012.
  3. D. Hubel, “Eye, Brain and Vision”, Scientific American Library, 1988, ISBN 0-7167-5020-1
  4. Nikos Paragio, Yunmei Chen, Olivier Faugeras, “Handbook of mathematical models in computer vision”, Springer, 2006
  5. Richard Hartley, Andrew Zisserman, “Multiple view geometry in computer vision” (2nd Edition), Cambridge university press, 2003
  6. Christopher M. Bishop, “Pattern recognition and machine learning”, Springer, 2006.
  7. David Marr, “Vision: A Computational Investigation into the Human Representation and Processing of Visual Information”, MIT Press, 2010.
  8. D.L.Baggio, etc. Mastering OpenCV with Practical Computer Vision Projects, 2012