Computer Vision and Intelligent Systems

ECG795 Spring 2013

Description

Professor:
Dr. Brendan Morris,
SEB 3216
OH: M-Th 15:00-16:00

Lecture: TuTh 17:30-18:45, WRI C225 FDH 204
Final: Tu May 16, 18:00-20:00
Look up your final exam schedule now to determine conflicts.

Textbook: Computer Vision: Algorithms and Applications, Richard Szeliski. Available online [link]
Recommended Text: Digital Image Processing, Gonzalez and Woods. Reference website [link]



Catalog Description:
Introductory graduate course in computer vision, machine leaning, and pattern recognition with real-time systems. The course will be divided into two parts: image and video processing. Image processing topics will include image formation, morphology and connected components, feature detection and representation, segmentation, and stereo imaging. Video processing techniques will focus on motion estimation, tracking, and object detection and recognition.

The course will have programming homework assignments and a final project. Readings will be assigned in ``Computer Vision: Algorithms and Applications'' by Richard Szeliski as well as recent papers from top academic publications.

Programming assignments will use Matlab as well as OpenCV.

Prerequisites: Linear Algebra and Programming Experience

Course Syllabus: [pdf]

Grading

ComponentPercentageDate
Final: 30% 05/16 18:00
Project: 30% 10/25
Homework: 40%
The course will have programming homework assignments and a final project. Students may work together in study groups but all assignments must be completed individually. Homework will be due in class on the designated date. No late homeworks will be accepted unless prior notification and arrangements are made.

Announcements

DateNote
05/032/13 Sample final questions [pdf] are available to study over the weekend.
03/18/13 Project information is now posted: description [pdf] ideas [pdf].
02/11/13 Data for homeworks can be found here [link]
02/04/13 Class is moved to FDH 204.
01/22/13 Welcome to Spring 2013.

Schedule (Tentative)

WeekDateLecture TopicReadingAssignment
1 01/22 Tu Course Introduction, Image Formation [pdf] Szeliski Ch 1, 2
01/24 Th Image Formation [pdf]
2 01/29 Tu Image Processing: Histogram Equalization, Filtering [pdf] Szeliski Ch 3
01/31 Th Image Processing: Smoothing and Sharpening [pdf]
3 02/05 Tu Morphology, Connected Components [pdf] Szeliski Ch 3 HW00 [pdf]
HW01 [pdf]
Due Th 02/21
02/07 Th Correlation Detection, Pyramids [pdf]
4 02/12 Tu Feature Detection and Matching: Points [pdf] Szeliski Ch 4
02/14 Th Feature Detection and Matching [pdf]
5 02/19 Tu Feature-Based Alignment and Edges [pdf] Szeliski Ch 6, 9
02/21 Th Image Alignment and Warping [pdf]
6 02/26 Tu Moasics and Panoramas [pdf] Szeliski Ch 11 HW02 [pdf]
Due Th 03/14
02/28 Th Epipolar Geometry and Homography [pdf]
7 03/05 Tu Stereo [pdf] Szeliski Ch 8
03/07 Th Motion Estimation [pdf]
8 03/12 Tu Motion Estimation
 Szeliski Ch 8
03/14 Th No Class
9 03/19 Tu Optical Flow [pdf] [Stauffer and Grimson 1999] [pdf]
03/21 Th Background Subtraction [pdf]
10 03/26 Tu Spring Break
 Project Description [pdf]
Project Ideas [pdf]
03/28 Th Spring Break
11 04/02 Tu Background Subtraction [pdf] Szeliski Ch 14
04/04 Th Object Recogntion Intro [pdf]
12 04/09 Tu Viola and Jones Face Detection by Jason Rock [ppt] [Viola and Jones 2001] [pdf]
[Turk and Pentland 1991] [pdf]
04/11 Th Eigenfaces by Yikun Jiang [ppt]
13 04/16 Tu Kalman Tracking by Mohammad Shirazi [ppt] [Koller et al. 1994] [pdf]
[Ng et al. 2001] [pdf]
04/18 Th Graph Cuts Spectral Segmentation by Ali Pouryazdanpanah [ppt]
14 04/23 Tu Vehicle and Lane Detection by Wenxin Peng [ppt] [Sivaraman and Trivedi 2013] [pdf]
[Anagnostopoulos et al. 2008] [pdf]
04/25 Th Licence Plate Recognition by Krikor Hovasapian
15 04/30 Tu Gesture Recognition by Carolina Vettorazzo and Diego Santo [ppt] [Patsadu et al. 2012] [pdf] Sample Final [pdf]
05/02 Th Project
16 05/07 Tu Final Review
05/09 Th Final
17 05/16 Th Project Presentations -