Page type: course

CS 766 - Computer Vision;CS 766 - Computer Vision;Fall 1995;Instructor: Chuck Dyer;Office: 6397 CSS;Telephone: 262-1965;Email: dyer@cs.wisc.edu;Office Hours: 2:30 - 3:30 Mondays and Thursdays, and by appointment;Teaching Assistant: Bryan So;Office: 5364 CSS;Telephone: 262-5105;Email: so@cs.wisc.edu;Office Hours: 1:00 - 2:00 Wednesdays and Fridays, and by appointment;Students; What's New?; General Course Information;Fundamentals of computer vision.;First, an introduction to low-level image analysis methods,;including image formation, edge detection, feature;detection, and segmentation.;Principles of defining modules for;reconstructing three-dimensional scene information using;techniques such as;shape from shading and depth from stereo.;Active methods for scene recovery such as depth from focus and;occluding contour detection by viewpoint control.;Motion detection and analysis including tracking.;Model-based three-dimensional object recognition.;Schedule; 1:00 - 2:15 p.m. Tuesdays and Thursdays in 1325 CSS; Prerequisites; CS 540, fundamentals of calculus, probability; theory, linear algebra, and C; Grading;Midterm Exam (Thursday, November 16): 35%; Homework assignments: 35%; Project: 25%; Class participation: 5%;;Syllabus;Required Readings;Selected parts of; Machine Vision; by R. Jain, R. Kasturi, and B. G. Schunck, McGraw-Hill,; New York, 1995; A collection of readings;from journals and conference proceedings;;to be sold at DOIT Documentation in small batches;Supplementary Reading Sources;Online Information;Most course information will be available online at WWW URL;http://www.cs.wisc.edu/~dyer/cs766.html; Reading Assignments to Date;9/5: Chapters 1 and 8 of JKS, and Paper #1 (at DOIT);9/14: Chapter 2;9/21: Chapter 3;9/28: Chapters 4 and 5;10/5: 4 papers at DOIT available as Handout #3;10/17: Chapter 6 except 6.6, 6.7, 6.8.3, and 6.9;10/19: Chapter 7.1 - 7.3, and 2 papers at DOIT available as Handout #4;11/2: 3 papers at DOIT available as Handout #5, and Chapters 9, 11.1 - 11.3;11/28: Chapter 14 (primarily 14.4);Student Scores and Grades; Homework Assignments;Homework #0: Image Enhancement by Histogram Modification (Optional);Make a copy of your portrait image in ~cs766-1/public/images/;and then use xv to contrast enhance your face. Do this by;first rotating the image, then cropping a window around your head;(say down to your shoulders), and finally interactively adjusting the;Intensity modification function in the Color Editor window under the;Windows button. (You are also free to modify other things such as color;if you wish.) When you have found a good grayscale transformation;save the result as a color gif image and;put it in the same directory where;the original image is. Send me email telling me qualitatively what;intensity transformation you applied and why it improves the quality;of the image overall. I'll then use this image in the "photo board";of students in the class. Feel free to use this image in your own;Web home page as well!;Homework #1: Skeletons (Due: October 3);;Learn about getting started with; the Vista vision software;Read the Introduction to Vista Programming manual; that is available at DOIT Documentation; Corrections to the Original Assignment;;In Method 1, change condition 1 to be "at least 3 ..."; instead of "at least 2 ..."; this will prevent some; types of shapes from disappearing altogether; In Method 1, condition 2 should also count as a 0-1 transition; the case where NW=0 and N=1; In Method 2, the 3 x 3 matrix c for city-block distance should have; infinity (i.e., some large constant), not 0, in the four corners; In Method 2, the 3 x 3 matrix c for chessboard distance should have; 0, not 1, in the center position;;TEST IMAGES to be used:; (1) /p/vision/images/hw1/DOIT.v; (2) /p/vision/images/hw1/hand.v;To evaluate your thinning results, you might want to; try the following additional experiment using the output of at least; one of your tests: (1) Convert your skeleton image to ubyte format using; vconvert, (2) edit (you may need to use Emacs because vi is; not "8-bit clean") the header of the new; image file so that it contains the following lines right after the; repn: ubyte line:; component_interp: gradient; low_threshold: 1; high_threshold: 2; (3) run vlink on this file, and then (4) vsegedges.; Try using the results on the image hand.v, for example, to; see how well this approach might be used to determine the direction; the index finger is pointing (for a HCI application, say).; Note: The thinning method may in fact delete entirely some shapes;; e.g., a 2 x 2 block of 1's surrounded by all 0's will disappear; The thinning algorithm is based on the papers: (1) T. Zhang and C. Suen,; A fast parallel algorithm for thinning digital patterns,; Comm. ACM 27(3), 1984, 236-239, and; (2) H. Lu and P. Wang, A comment on "a fast parallel algorithm; for thinning digital patterns," Comm. ACM 29(3),; 1986, 239-242.; Comparison of student results of the; different methods applied to the pointing hand image and a; rotated version of this test image;;Homework #2: Image Splining for Mosaics (Due: October 24);;Read the 3 papers:;;E. H. Adelson et al., Pyramid methods in image processing,; RCA Engineer 29-6, Nov/Dec 1984; P. Burt and E. H. Adelson, The Laplacian pyramid as a compact; image code, IEEE Trans. Comm. 31, 1983, 532-540; P. Burt and E. H. Adelson, A multiresolution spline; with application to image mosaics, ACM Trans. Graphics;2, 1983, 217-236;;Hints and FAQs;Some splined images; produced by students in the class;;Homework #3: Segmentation by Snakes (Due: November 9);;Read the 2 papers:;;M. Kass, A. Witkin and D. Terzopoulos,; Snakes: Active contour models,; Int. J. Computer Vision 1,; 1988, 321-331; D. Williams and M. Shah, A fast algorithm for active contours; and curvature estimation, Computer Vision, Graphics, and Image; Processing: Image Understanding 55, 1992, 14-26;;Hints and FAQs;Homework #4: Your Own Project (Due: December 18);; Student Project Titles and Abstracts; See Supplementary Readings; for some additional papers that might help you select a topic.; Student projects done in Stanford vision course; Computer Accounts;Accounts; Course accounts are on the Sun Sparcstations called sun1 - sun36; in rooms 1358, 1363 and 1368. Each account has a large disk space quota; of 50MB so you can store images for homeworks and; your project. Be sure to delete old images and compress others; (see gzip(1)), however,; in order to save space.; Email; Email sent to cs766-1list; goes to everyone in the class including the instructor and TA; Printers; To print images you should use one of the laserprinters,; laser1 - laser4, which are located; in room 1359. Alternatively, the generic printer name laser will; send output to one of the four printers with the shortest queue. Caution:; Before sending images to the printer, be sure to check the queue; if; there are a lot of jobs being printed it is bad manners to send images; to be printed because they take so long to print. Be considerate!;Vision Software; Vista; The Vista; programming environment will be used in the homework assignments.; The code is located in the directory /p/vision/ip-tools/vista/; Man pages are in /p/vision/ip-tools/vista/man/; and executables are in /p/vision/ip-tools/vista/bin/; Xv;xv(1) is an interactive image display program for the X; window system that is very useful for displaying images in a; variety of formats.; ImgStar; 70 basic image processing operations invoked using Unix-like command lines.; Code, executables and manual are in /p/vision/ip-tools/imgstar/; Khoros; The Khoros image processing software development environment; provides a set of basic image processing modules and a graphical; programming language interface for rapid prototyping of simple; image processing algorithms. The code is located in the directory; /p/vision/ip-tools/khoros /p/vision/ip-tools/khoros/bin/cantata; is the executable that starts up the interactive environment.; Netpbm; A toolkit for conversion of images between a large variety of; different formats. Based on the Pbmplus package. Man pages are in; /p/vision/ip-tools/man/ and executables are in; /p/vision/ip-tools/bin/; Matlab;Matlab(1) is a numeric computation and visualization; environment. Signal processing; and image processing toolboxes are especially relevant.;;Test Images; Most test images will be put in the directory; /p/vision/images/ although they may require format; conversion to be used. Some other images may be put in; ~cs766-1/public/images/ Numerous image databases are also; accessible via the WWW; for example, see the; collection of test images at CMU; Examination;Examination;Solution; The Exam will be held on Thursday, November 16 from 12:45 pm to 2:15 pm in the regular classroom, 1325 CS. Note the early; starting time! The exam will cover topics up through shape-from-shading,; including readings in the textbook, papers sold through DOIT, and; homework assignments. You may bring into the exam one (1) 8.5" x 11"; sheet of paper with any notes you want on both sides. The exam will; focus on main ideas and algorithms, not proofs. See old exams below for; the types of questions that will be asked.; Old Exams;;Exam 1 - Spring 1994;Exam 2 - Spring 1994;Exam 1 - Spring 1992;Exam 2 - Spring 1992; Links of Interest;Computer Vision Home Page (highly recommended!); Chuck Dyer's Links of Interest;B. Wandell's List of Useful Numbers in Vision Science;HDTV;;Grand Alliance HDTV System Specification;Advanced Television Systems Committee (ATSC);ATSC Documents in postscript;SPIE Optical Science and Engineering Library; Vision Demos and Projects;Apple's Quicktime VR image mosaicing product;IBM's PanoramIX image mosaicing;An Example of Panoramic Image Mosaicing;DECface talking synthetic face;CMU Video-Rate Stereo Machine;CMU Virtualized Reality Project;IBM's QBIC Image Database Project;Miscellaneous Computer Vision Demos; Other Computer Vision and Related Courses;CS 585 and CS 835 at Boston University; Cardiff University (UK);Khoros Digital Image Processing Online Course;Royal Institute of Sweden;Stanford University;University of Virginia;University of Washington;