Reconnaissance d’objets et vision artificielle 2009/2010

Object recognition and computer vision 2009/2010


Jean Ponce, Ivan Laptev, Cordelia Schmid and Josef Sivic



Course Information

The final project is out. See the project page here.

NEW Location Room: ENS Ulm, UV aile Rataud 45 rue Ulm
Class time: Tuesday 16:15-19:15

Course description

Automated  object  recognition -- and  more  generally  scene  analysis -- from  photographs  and 
videos  is  the  grand  challenge  of  computer  vision.  This  course  presents  the  image,  object,  and 
scene models, as well as the methods and algorithms, used today to address this challenge.

Assignments

There will be four programming assignments representing 70% of the grade.

1. Scale invariant feature detection. Hand out date: Oct 13th. New: Due date: Nov 03. 
2. Stitching photo mosaics. Hand out date: Oct 27th. Due date: Nov 10.
3. Bag-of-features image classification. Hand out date: Nov 10. Due date: Nov 24.
4. Simple face detector. Hand out date: Nov 24. Due date: Dec 8.

Final project

The final project is out now. Hand out date: Dec 1.  New: Due date extended: Jan 05th.

The final project will represent 30% of the grade.


Computer vision and machine learning talks

You are welcome to attend seminars in the Willow group. Please see the current seminar schedule.
Typically, these are one hour research talks given by visiting speakers.
The talks are at 23 avenue d'Italie. Ring the bell to get into the building, then take the elevator to the 5th floor.

Course schedule (subject to change)

Lecture
 Date
 		Topic
 		Slides
1
 Oct 6
 Introduction + Image alignment (Ivan Laptev)
 PPT PDF
2
 Oct 13
 Local invariant features (C. Schmid)
 PPT1 PPT2 PDF1 PDF2
3
 Oct 20
 Review of camera geometry; Image alignment 2D and 3D (J. Ponce)
 PPT PDF
4
 Oct 27
 Fitting (J. Ponce); Linear filtering - review (J. Sivic); Visual search (J. Sivic)
 PPT1 PPT2 PPT3  PDF1 PDF2 PDF3
5
 Nov 3
 Bag-of-feature models (C. Schmid) PPT1 PPT2 PPT3  PDF1 PDF2 PDF3
6
 Nov 10
 Face recognition and detection; Neural networks I. (J. Ponce) PPT PDF
7
 Nov 17
 Neural networks II.; Optimization methods; Part-based models (J. Ponce)
 PPT PDF
8
 Nov 24
 Sparse coding and dictionary learning for image analysis (J. Mairal). Based on ICCV'09 tutorial.
 PDF0 PDF1 PDF2 PDF3 PDF4 PDF5
9
 Dec 1
 Category level localization (C. Schmid) PPT1 PPT2  PDF1 PDF2
10
 Dec 8
 Review of dynamic programming; Pictorial structures; Character retrieval and annotation in video (J. Sivic) PDF1 PDF2 PDF3
11
 Dec 15
 Motion and human actions (I. Laptev)
 PPT1 PPT2 PDF1 PDF2


Relevant literature: