3D Vision (EE 569)

2014 Fall
Faculty of Engineering and Natural Sciences
Electronics Engineering(EE)
3
10
Mustafa Ünel munel@sabanciuniv.edu,
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English
Doctoral, Master
--
Formal lecture
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Programs\Type Required Core Elective Area Elective
Computer Science and Engineering - With Bachelor's Degree *
Computer Science and Engineering - With Master's Degree *
Computer Science and Engineering - With Thesis *
Cyber Security - With Bachelor's Degree *
Cyber Security - With Master's Degree *
Cyber Security - With Thesis *
Electronics Engineering and Computer Science - With Bachelor's Degree *
Electronics Engineering and Computer Science - With Master's Degree *
Electronics Engineering and Computer Science - With Thesis *
Electronics Engineering - With Bachelor's Degree *
Electronics Engineering - With Master's Degree *
Electronics Engineering - With Thesis *
Energy Technologies and Management-With Thesis *
Industrial Engineering - With Bachelor's Degree *
Industrial Engineering - With Master's Degree *
Industrial Engineering - With Thesis *
Leaders for Industry Biological Sciences and Bioengineering - Non Thesis *
Leaders for Industry Computer Science and Engineering - Non Thesis *
Leaders for Industry Electronics Engineering and Computer Science - Non Thesis *
Leaders for Industry Electronics Engineering - Non Thesis *
Leaders for Industry Industrial Engineering - Non Thesis *
Leaders for Industry Materials Science and Engineering - Non Thesis *
Leaders for Industry Mechatronics Engineering - Non Thesis *
Manufacturing Engineering - Non Thesis *
Manufacturing Engineering - With Bachelor's Degree *
Manufacturing Engineering - With Master's Degree *
Manufacturing Engineering - With Thesis *
Materials Science and Nano Engineering-(Pre:Materials Science and Engineering) *
Materials Science and Nano Engineering-(Pre:Materials Science and Engineering) *
Materials Science and Nano Engineering - With Thesis (Pre.Name: Materials Science and Engineering) *
Mechatronics Engineering - With Bachelor's Degree *
Mechatronics Engineering - With Master's Degree *
Mechatronics Engineering - With Thesis *
Molecular Biology, Genetics and Bioengineering (Prev. Name: Biological Sciences and Bioengineering) *
Molecular Biology, Genetics and Bioengineering-(Prev. Name: Biological Sciences and Bioengineering) *
Molecular Biology,Genetics and Bioengineering-With Thesis (Pre.Name:Biological Sciences and Bioeng.) *
Physics - Non Thesis *
Physics - With Bachelor's Degree
Physics - With Master's Degree

CONTENT

This course deals with a central problem in vision -how to recover 3-D structure and motion from a collection of 2-D images-using techniques mainly from linear algebra and matrix theory. Topics included are: geometric image formation, camera models, image feature extraction and tracking, camera calibration, stereo, epipolar geometry, eight-point algorithm, 3D reconstruction from two or more images, motion estimation etc. The aim is to provide graduate students in EE, CS and ME with a solid theoretical and algorithmic background for research.

OBJECTIVE

Objective of the course is to develop a unified framework for studying the geometry of multiple images of a 3-D scene and reconstructing geometric models from those images. Additionally the course provides graduate students with a solid theoretical and algorithmic background for research.

LEARNING OUTCOMES

  • On successful completion of the course, students will be able to: - Use various camera models in different applications
  • - Extract important image features and track them in real-time
  • - Compute optical flow
  • - Calibrate cameras
  • - Estimate camera motion and 3D structure
  • - Understand basics of multi-view geometry

ASSESSMENT METHODS and CRITERIA

  Percentage (%)
Individual Project 50
Homework 50

RECOMENDED or REQUIRED READINGS

Textbook

An Invitation to 3-D Vision: From Images to Geometric Models, Y. Ma, S. Soatto, J. Kosecka, S. S. Sastry, Springer, 2005
Optional Readings

- Computer Vision: Algorithms and Applications, R. Szeliski, Springer, 2010
- Multiple View Geometry in Computer Vision, 2nd Edition, R. Hartley and A. Zisserman, Cambridge Univ. Press, 2003
- Computer Vision: A Modern Approach, D. A. Forsyth and J. Ponce, Prentice-Hall, 2003 (available as pdf)