Structured Computer Vision CS 276B
Fall 1996 Allen Klinger
Class Meetings Tuesday/Thursday 8-10 AM Room 2242, Public Policy
Readings in Text and Recommended Book - see Course Outline (below)
Lectures include 1) discussion; and 2) student presentation of text and research reading.
Research familiarization, a course purpose; goal - to read two recently-published journal items..
Written/Oral Reporting Mid-quarter outline/summary, summary project/review paper.
Presentations, Problems 20 solved problems due last class with paper. Text, homework- problem explanation or paper-read talk and project presentation last four weeks.
Examinations Occasional quizzes. Midterm long-quiz.
Office, E-Mail, Phone 3531-H Boelter Hall <klinger@cs.ucla.edu> 310 825-7695
Secretary Room 3532-F Phone 310 825-1322
Text: V. Nalwa, A Guided Tour of Computer Vision,
Addison-Wesley, 1993, ISBN 1-201-54853-4.
Recommended: H. Samet, The Design and Analysis of Spatial Data Structures,
Addison-Wesley, 1990, ISBN 0-201-50255-0.
Some Journals: IEEE Transactions (Pattern Analysis Machine Intelligence, Biomedical Engineering, Robotics and Automation, Image Processing, Systems Man Cybernetics), Int. J. Artificial Intelligence Tools, Computer Vision Graphics and Image Processing
Books:
Haralick, R., Shapiro, L., Computer & Robot Vision I-II
Shirai, Three Dimensional Computer Vision
Fischler/Firschein eds. Readings in Computer Vision
Jain, R., et.al., Machine Vision
Samet, H., Applics. of Computer Graphics, Image Processing & Geographic Information Systems
Kunii, T., ed. Visual Database Systems
Fu/Kunii eds. Picture Engineering
Tanimoto, S., Klinger, A., eds. Structured Computer Vision
Klinger, A., et. al., eds. Data Structures, Computer Graphics & Pattern Recognition
Rosenfeld, A., ed. Multiresolution Image Processing and Analysis
Structured Computer Vision CS 276B
Fall 1996 Allen Klinger
I. Computer Vision for Robotic, Industrial and Medical Applications
Image and Spatial Computational Geometry
Data Structures and Algorithms
Quadtrees
Shape Analysis
Representaion Methods
II. Image Analysis Procedures
Image Feature Extraction
Computer Processing to Find and Use Points and Lines
Locating, Measuring and Storing Areas and Area-Properties
Regions - Characterization and Use
. Enhancing Image Quality
III. Statistical and Recursive Computations
Neighborhood Selection and Adaptation
Hierarchical Algorithms
Segmentation
Texture Measurement
Fractals, Chaos, Order and Randomness
IV. Computational Issues
Computational Geometry
Planar Tesselations
Digital Images - Compression, Utilization
Transmission of Images
Image Databases
Structured Computer Vision CS 276B
Fall 1996 Allen Klinger
Week - Class Meets Topic Read (Ch: pp.) Project/Talk
Text: V. Nalwa, A Guided Tour of Computer Vision;
Recommended: H.Samet, The Design and Analysis of Spatial Data Structures: SDS.
Low-Level
1 - 9/26, 10/1 Introduction, Sensing 1: 3- 30; 2: 54 64 Practice/Theory
2 - 10/3, 8 Edge Detection 3: 75-107 7: Correspondence
3 - 10/10, 15 Region-Growing 3: 113-126 8: Motion
Intermediate-Level
4 - 10/17, 22 Line Drawings 4: 129-158 Outline/Summary
5 - 10/24, 29 Quaternary Trees SDS 1: 1-15, 32-41 Paper
6 - 10/31, 11/5 Shape 9: 285-310 Program
High-Level & Global
7 - 11/7, 12 Solid Modeling SDS 5: 315-338 Present Results
8 - 11/14, 19 Shading 5: 161-165; SDS 2: 48-53 Key Theme
9 - 11/26 Texture and Tiling 6: 187-198; Accomplishments
10 - 12/3, 5 Projection 6: 198-216 Report 12/5
9/14/1999 Version