Stat 238

Vision as Bayesian Inference

Tu/Thurs: 9:30-10:50am Winter 2009, Geology 4635.
 
www.stat.ucla.edu/~yuille/Courses/UCLA/Stat_238/Stat_238.html.
 

Course Description

This course models vision as Bayesian Inference. It concentrates on visual tasks such as segmenting images, detecting objects in images, and recognizing objects. Its goal is to describe the state of the art techniques. The handouts consist of copies of the lecture notes and related papers.

Reading Material

Grading Plan: 3  homework assignments (20% each). Term project (40%).

Tentative Schedule.

Lecture

Date

Topics

Reading Materials

Handouts

1

01-06

Introduction to the Course:
Statistical Edge Detection

statistical_regions.pdf

  chp1.pdf

2

01-08

Piecewise Smooth Image Models:
Geman & Geman

segmentation_overview.pdf

  chp2.pdf

3

01-13

Learning MRF models :
without hidden variables.

GYtics.pdf

chp3.pdf

4

01-15

            Basic Inference Algorithms.
                     Iterative, Variational, & MCMC

 

   chp4.pdf

5

01-20

Distributions with Hidden States:
Dynamic Programming

 

  chp5.pdf

     6

01-22

                   
       Hidden Markov Models:
 

chang_peng_2002_2.pdf

 chp6.pdf

     7

01-27

                   
                    Snakes & Region Competition

region_competition_pami.pdf

 chp7.pdf

8

01-29

                    
                    Active Bases (Y. Wu):

 

 ywu.pdf

9

02-03

                    Discriminative Random Fields:
                    Max-Flow/Min-Cut BP.

paper_siggraph04.pdf

chp9.pdf

10

02-05

 

               Hierarchical Models (SWA)

 

chp10.pdf

11

02-10

                 Lighting Models

 

chp11.pdf

12

02-12

 
                  Shape Models
 

fergus03object.pdf

Fergus_ECCV4.pdf

hand_cviu00J.pdf

notes10.pdf

notes11.pdf

13

02-17

 
                Object Models with Interest Points

C9_lzhu_PAMISUB2007.pdf

notes12.pdf

14

02-19

AdaBoost and SVM

 

summerschool1.pdf

15

02-24

Grammatical Models

 

 

16

02-26

POMs

pom_pami_alan_f.pdf

 

17

03-03

Image Parsing:      .

 

notesDPA.pdf

18

03-05

Hierarchical Models.

HLLM08pami_Alan.pdf

RCM_sum.pdf

19

03-10

 
Assorted Topics.

 

 

20

03-12

Review of Course 

 

 

   

 

 

 

 

 

 

Final Project Due 20/March. Hand in to Prof. Yuile. Office or Mailbox