Module 25024 (2012)
Syllabus page 2012/2013
06-25024
Robot Vision
Level 4/M
Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus
The Module Description is a strict subset of this Syllabus Page. (The University module description has not yet been checked against the School's.)
Relevant Links
None.
Outline
Vision is one of the major senses that enables humans to act (and interact) in (ever)changing environments. In a similar vein, computer vision should play an equally important role in relation to intelligent robotics. This module will focus on the fundamental computational principles that enable to convert an array of picture elements into structural and semantic entities necessary to accomplish various perceptual tasks. In a series of lectures, we will study the problems of low level image processing, recognition, categorisation, stereo vision, motion analysis, tracking and active vision. The lectures will be accompanied by a series of laboratory exercises where many of these computational models will be designed, implemented and tested in real-world scenarios.
Aims
The aims of this module are to:
- give an appreciation of the issues that arise when designing computational models that convert visual signals to structural and symbolic descriptions
- provide an understanding of the state-of-the-art methods and techniques for processing visual information
- give hands on experience of designing, implementing and testing computer vision algorithms in realistic scenarios
- encourage independent thought on deep scientific issues related to visual cognition
Learning Outcomes
| On successful completion of this module, the student should be able to: | Assessed by: | |
| 1 | design, implement and test simple computer vision algorithms | Team project |
| 2 | write a detailed report on a computer vision project | Team project |
| 3 | survey and critically discuss the research literature in one subfield of computer vision | Presentation |
| 4 | demonstrate an understanding of the main computer vision methods and computational models | Team project, examination |
Restrictions, Prerequisites and Corequisites
Restrictions:
None
Prerequisites:
None
Co-requisites:
None
Teaching
Teaching Methods:
2 hrs lectures per week, 4 student presentations, laboratory sessions
Contact Hours:
Assessment
- Sessional: 1.5 hour examination (40%), Continuous assessment (team project and presentation) (60%)
- Supplementary (where allowed): By repeat only.
Recommended Books
| Title | Author(s) | Publisher, Date |
| Computer Vision - A Modern Approach | D. Forsyth, J. Ponce | Prentice Hall, 2002 |
| Computer Vision - Algorithms and Applications | R. Szeliski | Springer, 2010 |
| Multiple View Geometry in Computer Vision | R. Hartley, A. Zisserman | 2nd Edition, Cambridge University Press, 2004 |
| Object Categorization: Computer and Human Vision Perspectives | S. Dickinson, A. Leonardis, B. Schiele and M. J. Tarr (Editors) | Cambridge University Press, 2009 |
Detailed Syllabus
-
Introduction
- Why computer/robot vision
- Applications
- Computer and human vision perspectives
- Challenges
- Image formation, low level image processing
- Image acquisition
- Noise removal (Linear filters, Median filter)
- Edge detection
- Structure extraction
- Parametric fitting
- Hough transform
- RANSAC
- Segmentation
- Clustering
- K-means
- Mean-shift
- Graph-cuts
- Local features
- Interest points
- Harris detector, Hessian detector
- SIFT
- 3D reconstruction
- Stereo vision
- Correspondence
- Epipolar geometry
- Recognition
- Histograms
- Subspace representations
- Principal component analysis
- Categorization
- Bag-of-features
- Part-based methods
- Deformable part-based detector
- Hierarchical compositional architectures
- Motion and tracking
- Optical flow
- Tracking as detection
- Kalman filter
- Active vision
- Perception-action cycle
- Attention
- Visual servoing
Last updated: 10 May 2012
Source file: /internal/modules/COMSCI/2012/xml/25024.xml
Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus