CSCI 508 / EENG 508 - Schedule

Semester: Spring 2017

Homeworks are due by the beginning of class on the indicated due dates.
Unless otherwise specified, "Ref" numbers are chapters or sections in the Szeliski book.

Week	Day	Due	*Ref*	Main Topics	Materials	Lab
1	1/12		Ch 2	Review and background	Course introduction (slides) Review of selected computer vision topics (slides) OpenCV code (Source.cpp)	L1
2	1/17	H0	App A,B		Review of probability (slides) Singular value decomposition (slides)
	1/19		App B		Uncertainty estimation (slides) Images: book_A.jpg, book_B.jpg, img1_rect.tif	L2
3	1/24	H1	14.3.1	Model Based Recognition	Model based recognition (slides) Interpretation tree demo: interptree.m
	1/26		7.2	Multiview Geometry	Essential matrix (slides)
4	1/31	P1		LaTex tutorial	Software (slides) Tutorial (slides, example files)
	2/2		7.2		Structure from motion (slides) Matlab program (twoview.m) Fundamental matrix (slides)	L3
5	2/7	H2			Notes RANSAC and the fundamental matrix (slides) Matlab code (fitFundamental.m, fundRANSAC.m) Bundle adjust (slides)
	2/9				SfM demo using Matlab tools (slides)	L4
6	2/14	P2			Final project info (slides) Stereo vision (slides) Images: scene1.row3.col1.ppm, scene1.row3.col3.ppm, truedisp.row3.col3.pgm Matlab code: stereo_BasicBlockMatch.m, stereo_BlockMatchDynamicProg.m
	2/16		4.1	Local Features	Notes Local features (slides)	L5
7	2/21	H3		No class - Presidents Day
	2/23	Proj prop			Training feature recognizers (slides) Contour features (slides) Matlab code (chamfer.m, visualizeFit.m) Images (hand_image.png, hand_templates.zip)
8	2/28	P3	5.1	Shape and Appearance Models	Deformable models (slides) Matlab code (mysnake.m), image (Unwarp_B_Cormier_L_30.tif) Intro to Machine Learning for Computer Vision (slides) Matlab code (class_gen.m)
	3/2		14.2		Guest speaker: Dr. Josh Gordon from NIST Statistical models (slides)
9	3/7	H4		Classifers and Recognition	Classification (slides) Pool ball identification (slides) Movies: TableA_movie1, TableA_movie2, TableA_movie3, TableA_movie4 TableB_movie1, TableB_movie2, TableB_movie3
	3/9		14.1		Continue with pool ball identification exercise Histogram of Oriented Gradients (slides)	L6
10	3/14	P4			Notes on project progress presentations (slides) People detection (slides) Sample images from Graz 01 database (graz.zip)
	3/16				Boosting classifiers (slides) Brown Hall sign images: trainingPositive, trainingNegative, testImages
11	3/21			Project Progress Presentations	Instructions and schedule (slides)
	3/23			Project Progress Presentations	Instructions and schedule (slides)
	3/28			No class - spring break
	3/30			No class - spring break
12	4/4		5.3	Segmentation	Basic Segmentation (slides) Matlab code (GMMExample_2D.m)
	4/6		5.5		Graph Cuts (slides) OpenCV demo program (doGrabCut.cpp)	L7
13	4/11		14.3, 14.4	Indexing and Category Recognition	Recognition in large databases (slides)
	4/13				Upcoming seminars of interest (slides) Category recognition (slides)	L8
14	4/18	H5		Deep Learning	Guest speaker: Youye Xie Tutorial on deep learning (tutorial1, tutorial2)
	4/20				Neural networks in Matlab (slides)	L9
15	4/25			Project meetings
	4/27	P5		Project meetings
16	5/2			Final Project Presentations	Schedule and guidelines (slides)
	5/4			Final Project Presentations	Schedule and guidelines (slides)