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2015HS: 31062 Computer Vision

This course covers fundamental topics in computer vision. The course will provide an introduction to image formation, image processing, feature detection, segmentation, multiple view geometry and 3D reconstruction, motion, object recognition and classification.

Allgemeine Informationen

Kursbeschreibung
The following books are recommended as additional reading:
• Computer Vision : A Modern Approach, David A. Forsyth and Jean Ponce.
• Algorithms and Applications, Rick Szeliski.
An electronic copy is also available free online (http://szeliski.org/Book/).
• Visual Object Recognition, Kristen Grauman and Bastian Leibe.
This book is also available online for free.


The exercises are a prerequisite for registering for the exam. There will be several homework assignments and the deadlines will be specified by the teaching assistant. For admission to the examination one must pass every assignment. The assignments will also contribute to 30% of the final mark. The description of each assignment will be made available in Ilias. Notice that assignments will require use of Matlab. All the homework assignments are also intended for exam preparation.
Kursprogramm
The course requires students to be familiar with the basics of linear algebra, probability theory and Matlab programming. A brief review of these subjects will be carried out during the exercise sessions.

Syllabus

Early vision
Introduction & projection models (date: 16/09, book: Forsyth & Ponce Ch 1)
Camera models, radiometry & shading (date: 23/09, book: Forsyth & Ponce Ch 1 & 2)
Photometric stereo & uncalibrated photometric stereo (date: 30/09, book: Forsyth & Ponce Ch 2)

Features and geometry
Linera filters, edges (date: 7/10, book: Forsyth & Ponce Sec 4, 5.1, 5.2 & 5.3)
Interest points detection and Fitting (date: 14/10, book: Forsyth & Ponce Ch 10)
Epipolar geometry & stereo (date: 21/10, book: Forsyth & Ponce Sec 7.1)
Multiview stereo and structure from motion (date: 28/10, book: Forsyth & Ponce Ch 7 & 8)

Classification
Recognition & machine learning (date: 4/11, book: Grauman & Leibe)
Bag of words & support vector machine (date: 11/11, book: Forsyth & Ponce Ch 15 & 16)
Deformable part-based models (date: 18/11, book: Grauman and Leibe)

Grouping and motion
Tracking, optical flow & registration (date: 25/11, book: Forsyth & Ponce Sec 1.1)
Clustering and segmentation (date: 2/12, book: Forsyth & Ponce Ch 9)
Special topic: Inverse Problems and Regularization (date: 09/12)
Revision (date: 16/12, source:Handouts)

Beschreibung

This course covers fundamental topics in computer vision. The course will provide an introduction to image formation, image processing, feature detection, segmentation, multiple view geometry and 3D reconstruction, motion, object recognition and classification.

Allgemein

Sprache
Englisch
Copyright
This work has all rights reserved by the owner.

Kontakt

Name
Prof. Dr. Paolo Favaro
Zuständigkeit
Lecturer
E-Mail
favaro@iam.unibe.ch

Verfügbarkeit

Zugriff
Unbegrenzt – wenn online geschaltet
Aufnahmeverfahren
Sie können diesem Kurs direkt beitreten.
Zeitraum für Beitritte
Bis: 1. Okt 2015, 00:00

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