Computer Vision (EE 417)

2022 Fall
Faculty of Engineering and Natural Sciences
Electronics Engineering(EE)
3
8/6 ECTS (for students admitted in the 2013-14 Academic Year or following years)
Mustafa Ünel munel@sabanciuniv.edu,
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English
Undergraduate
CS201
Formal lecture,Laboratory
Interactive,Discussion based learning,Project based learning,Simulation,Case Study
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Programs\Type Required Core Elective Area Elective
Computer Science and Engineering *
Computer Science and Engineering *
Electronics Engineering *
Electronics Engineering *
Materials Science and Nano Engineering *
Materials Science and Nano Engineering (Previous Name: Materials Science and Engineering) *
Mechatronics Engineering *
Mechatronics Engineering *
Microelectronics *
Telecommunications *

CONTENT

Introduction to Computer Vision, Human Visual System, Image Formation, Pointwise Image Operations, Image Intensity Transformations, Geometric/Coordinate Transforms, Interpolation, Image Neighborhood Operations, Spatial Filtering, Edge Detection, Feature Extraction, Principal Component Analysis and Applications, Morphological Image Processing, Basic Segmentation, Thresholding techniques, Motion/Dynamic Scenes, Color and texture, Object/Shape Modeling / Recognition

OBJECTIVE

To teach the fundamentals of computer vision, which tries to make computers see and interpret the world.

LEARNING OUTCOMES

  • Upon successful completion of EE 417 Computer Vision, students are expected to be able to: - Discuss the main problems of computer vision, its uses and applications
  • - Design and implement various image transforms: point-wise transforms, neighborhood operation-based spatial filters, and geometric transforms over images
  • - Design and implement several feature extraction algorithms including edges and corners
  • - Design and implement line and circle detection using Hough transform
  • - Calibrate real cameras and determine both intrinsic and extrinsic parameters,
  • - Formulate and solve 2D optic flow problem
  • - Establish correct correspondence for stereo images using a correlation based matching technique
  • - Estimate the essential/fundamental matrix and determine extrinsic parameters (rotation and translation) of a stereo vision system
  • - Reconstruct 3D structure from 2D images using estimated extrinsic parameters
  • - Identify or recognize objects from images

PROGRAMME OUTCOMES

1. Understand the world, their country, their society, as well as themselves and have awareness of ethical problems, social rights, values and responsibility to the self and to others. 1

2. Understand different disciplines from natural and social sciences to mathematics and art, and develop interdisciplinary approaches in thinking and practice. 5

3. Think critically, follow innovations and developments in science and technology, demonstrate personal and organizational entrepreneurship and engage in life-long learning in various subjects; have the ability to continue to educate him/herself. 5

4. Communicate effectively in Turkish and English by oral, written, graphical and technological means. 5

5. Take individual and team responsibility, function effectively and respectively as an individual and a member or a leader of a team; and have the skills to work effectively in multi-disciplinary teams. 5

1. Possess sufficient knowledge of mathematics, science and program-specific engineering topics; use theoretical and applied knowledge of these areas in complex engineering problems. 5

2. Identify, define, formulate and solve complex engineering problems; choose and apply suitable analysis and modeling methods for this purpose. 5

3. Develop, choose and use modern techniques and tools that are needed for analysis and solution of complex problems faced in engineering applications; possess knowledge of standards used in engineering applications; use information technologies effectively. 5

4. Have the ability to design a complex system, process, instrument or a product under realistic constraints and conditions, with the goal of fulfilling specified needs; apply modern design techniques for this purpose. 4

5. Design and conduct experiments, collect data, analyze and interpret the results to investigate complex engineering problems or program-specific research areas. 4

6. Possess knowledge of business practices such as project management, risk management and change management; awareness on innovation; knowledge of sustainable development. 2

7. Possess knowledge of impact of engineering solutions in a global, economic, environmental, health and societal context; knowledge of contemporary issues; awareness on legal outcomes of engineering solutions; knowledge of behavior according to ethical principles, understanding of professional and ethical responsibility. 2

8. Have the ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions. 4

1. Design, implement, test, and evaluate a computer system, component, or algorithm to meet desired needs and to solve a computational problem. 5

2. Demonstrate knowledge of discrete mathematics and data structures. 5

3. Demonstrate knowledge of probability and statistics, including applications appropriate to computer science and engineering. 5

1. Use mathematics (including derivative and integral calculations, probability and statistics, differential equations, linear algebra, complex variables and discrete mathematics), basic sciences, computer and programming, and electronics engineering knowledge to (a) Design and analyze complex electronic circuits, instruments, software and electronics systems with hardware/software or (b) Design and analyze communication networks and systems, signal processing algorithms or software 5

1. Applying fundamental and advanced knowledge of natural sciences as well as engineering principles to develop and design new materials and establish the relation between internal structure and physical properties using experimental, computational and theoretical tools. 1

2. Merging the existing knowledge on physical properties, design limits and fabrication methods in materials selection for a particular application or to resolve material performance related problems. 1

3. Predicting and understanding the behavior of a material under use in a specific environment knowing the internal structure or vice versa. 1

1. Familiarity with concepts in statistics and optimization, knowledge in basic differential and integral calculus, linear algebra, differential equations, complex variables, multi-variable calculus, as well as physics and computer science, and ability to use this knowledge in modeling, design and analysis of complex dynamical systems containing hardware and software components. 5

2. Ability to work in design, implementation and integration of engineering applications, such as electronic, mechanical, electromechanical, control and computer systems that contain software and hardware components, including sensors, actuators and controllers. 5

ASSESSMENT METHODS and CRITERIA

  Percentage (%)
Midterm 35
Assignment 35
Group Project 30

RECOMENDED or REQUIRED READINGS

Textbook

Concise Computer Vision: An Introduction into Theory and Algorithms, Reinhard Klette, Springer, 2014. ISBN 978-1-4471-6319-0
Optional Readings

Computer Vision: Algorithms and Applications, R. Szeliski, Springer, 2010