ECEn 631 Course Syllabus

Robotic Vision

Offered in Winter Semesters



Dr. D. J. Lee


CB 453


(801) 422-5923


Course Overview

            Human vision is natural and seems to be able to process visual information effortlessly. Human vision is able to detect, localize, and recognize specific objects. Human vision is able to perceive and understand surrounding 3-D world and use the 3-D information to accomplish many complicated tasks. However, computer mimicry of human vision is difficult and often impossible.   The main properties of 3-D world are geometric and dynamic. The objectives of 3-D computer vision are to compute these properties from one or multiple digital images and to use them to mimic human vision. Basic image processing and feature detection techniques, camera models, geometry, and calibration, and geometrical models of single, two, and multiple view systems are three components of 3-D computer vision and they will be studied in this course.

The primary purpose of this course is not to give an exhaustive review of image processing techniques, but to cover methods commonly found in 3-D vision such as dealing with image noise, feature extraction, 3-D object representation and image matching.   A few mathematical concepts that are crucial to understanding of solutions and algorithms will be reviewed to the level of detail necessary to understand the material covered in this course.   Computer vision, like other engineering disciplines, has to ground itself in mathematics to study or solve its problems.    For each problem analyzed in this course, a theoretical treatment of the problem and the mathematical model will be shown and algorithms to the solutions of the problem will be derived.    The practical applicability of the 2-D and 3-D vision algorithms will also be discussed as case studies.


This course requires extensive software programming work. Students lack of skill or background in any of the following areas should not take this course.
    – C++ and Java programming experience
    – Familiar with Visual Stuido and Android Studio programming enviroments
    – Math and signal processing (ECEn 380)
    – Computer Systems (ECEn 424)
    – Real-Time Operating Systems (ECEn 425)
    – Embedded Systems (ECEn 427)

Course Objectives

Six main objectives of this course are
    – Learn machine vision system design and applications
    – Understand camera geometry and calibration
    – Learn feature detection and tracking
    – Extract 3-D information from single, two, and multiple views
    – Estimate camera and object motion
    – Learn to use OpenCV to implement real-time vision algorithms


Machine Vision, 3rd Edition
E.R. Davies

Elsevier, 2005

Introductory Techniques for 3-D Computer Vision
Emanuele Trucco & Alessandro Verri

Prentice Hall, 1998

An Invitation to 3-D Vision - From Images to Geometric Models
Yi Ma, Stefano Soatto, Jana Kosecka, & Shankar Sastry

Springer-Verlag, 2004

Multiple View Geometry in Computer Vision
Richard Hartley & Andrew Zisserman

Cambridge University Press, 2003

An Introduction to 3D Computer Vision Techniques and Algorithms
Boguslaw Cyganek & J. Paul Siebert

Wiley, 2009

3D Computer Vision: Efficient Methods and Applications
Christian Whler

Springer-Verlag, 2009


          >= 93: A     >= 90: A-     >= 85: B+     >= 80: B     >= 75: B-    >= 70 : C    >= 60 : D    <60 : E

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Student With Disabilities

Brigham Young University is committed to providing a working and learning atmosphere which reasonably accommodates qualified persons with disabilities.  If you have any disability which may impair your ability to complete this course successfully, please contact the Services for Students with Disabilities Office at 378-2767.  Reasonable academic accommodations are reviewed for all students who have qualified documented disabilities.  Services are coordinated with the student with the instructor by the SSD Office.  If you need assistance or if you feel you have been unlawfully discriminated against on the basis of disability, you may seek resolution through established grievance policy and procedures.  You should contact the Equal Employment Office at 378-5895, D-282 ASB.

Last modified: October 10, 2015.

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