Description:

The topics covered by this course include digital image formation, image features and feature detection, structure from X, image segmentation, object recognition, motion analysis, and stereopsis. Students will also work in groups to solve some real world problems. Some potential project topics are automatic object recognition, human face detection, video surveillance, and content-based image retrieval.

Syllabus:

1. Introduction
2. Image and video acquisition
3. Camera models
4. Image features - edge, corners, lines, Hough Transform, deformable contours
5. Camera calibration
6. Camera motion estimation and 3D scene reconstruction
7. Stereopsis
8. 2D motion analysis - optical flow estimation, differential techniques
9. Shape from X - reflection model, shape from shading, shape from texture, shape from defocusing and focusing
10. Tracking - Kalman filtering, correlation-based tracking, change-based tracking, 2D layer tracking, tracking of articulated objects
11. Image segmentation
12. Object recognition - Feature, invariants, subspace method, face detection and recognition

Reference:

Computer Vision -- A modern approach, by David Forsyth and Jean Ponce, Prentice Hall, 2002.

Time and Place:

TuTh   16:00 p.m. - 17:45 p.m.,   Crown College 104

Instructor:

Hai Tao (http://www.soe.ucsc.edu/~tao/)
Email:   tao@soe.ucsc.edu
Office:  Baskin Engineering  309A

Evaluation: Coursework will be weighted as follows:

 Homework   30%
 Mid-term      30%
 Project          40%

Homework: Homework will be collected every week on Thursday at the end of the class.

Homework Assignments: see notes

Lecture notes:

     Lecture 1,

     Lecture 2,3,

     Lecture 4,

     Lecture 5,

     Lecture 6,

     Lecture 7,

     Lecture 8,

     Lecture 9,

     Lecture 10,

     Lecture 11,

     Lecture 12,

     Lecture 13,

     HomeworkSolution,

     Lecture 14,

     Lecture 15,

     Lecture 16,

     Lecture 17,

     Lecture 18,

     Lecture 19,

     Lecture 20,

     Lecture 21,

Some Project Topics:

• 3D reconstruction and camera motion analysis

• Resolution enhancement

• Multiple view tracking

• Object tracking with occlusion

• Face detection

• Facial feature detection

• Facial motion analysis and event detection

• Image-based realistic facial animation

• Content-based image retrieval

• Image-based relighting

• A marker-driven pointing device

• Optical flow estimation

• Shape from brightness functions

Computer vision links:

• CMU Computer Vision Home Page
• CVonline: Computer Vision Online Course Notes
• USC Annotated Computer Vision Bibliography
• PEIPA - the Pilot European Image Proecssing Archive

Class Photo: small, full size.

webmaster@cse.ucsc.edu

Back to the SOE Class Home Pages.
Back to the SOE Home Page.