Graduate study programme

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Robot Vision DR4I-07

ECTS 5 | P 30 | A 0 | L 30 | K 0 | ISVU 62306 149808 | Academic year: 2019./2020.

Course groups

Prikaži sve grupe na predmetu

Course lecturers

CUPEC ROBERT, Lecturer
NYARKO EMMANUEL-KARLO, Associate

Goals

Gain basic knowledge from the field of computer vision. Provide an insight into possibilities of application of computer vision for object recognition, robot manipulation and localisation of autonomous mobile systems. Make students understand the basic principles of modern computer vision methods, and teach them to apply these methods for solving technical problems, which require object recognition, robot manipulation and localisation of autonomous mobile systems. Learn how to develop computer programmes based on computer vision.

Conditions for enrollment

Requirements met for enrolling in the second year of the study programme

Course description

Introduction to robot vision: basic terms, application of computer vision in robotics, examples. Image filtering. Edge and corner detection. Hough transform. Recognition of two- and three-dimensional objects. Camera model. Camera calibration. Stereo vision. Optical flow. Estimating camera pose relative to the operating environment of a robot. Multiple view of a three-dimensional object and scene reconstruction. Fusion of measurement data obtained by sensors of different types. Environment map building using data obtained by a vision system. Uncertainty of vision-based measurement. Application of computer vision methods for manipulation with objects in robotised production systems and navigation of mobile robots in their operating environments. 3D cameras. Segmentation of range images and 3D point clouds. Object recognition and pose estimation using a 3D camera.

Student requirements

Defined by the Student evaluation criteria of the Faculty of Electrical Engineering, Computer Science and Information Technology Osijek and paragraph 1.9

Monitoring of students

Defined by the Student evaluation criteria of the Faculty of Electrical Engineering, Computer Science and Information Technology Osijek and paragraph 1.9

Obligatory literature

1. 1 Bradski, G.; Kaehler, A. Learning OpenCV O Reilly, 2008


Pretraži literaturu na:

Recommended additional literature

1. 1 E. R. Davies Machine Vision: Theory, Algorithms, Practicalities, 3rd edition Elsevier, San Francisco, USA, 2005

2. 2 R. Hartley, A. Zisserman Multiple View Geometry in Computer Vision Cambridge University Press, 2003.

3. 3 O. Faugeras Three-Dimensional Computer Vision: A Geometric Viewpoint Cambridge, Massachusetts: The MIT Press, 1993.

4. 4 R. Cupec Osnove inteligentnih robotskih sustava, udžbenik u izradi Zavod za računalno inženjerstvo i automatiku, ETF Osijek, 2014.

Course assessment

Conducting university questionnaires on teachers (student-teacher relationship, transparency of assessment criteria, motivation for teaching, teaching clarity, etc.). Conducting Faculty surveys on courses (upon passing the exam, student self-assessment of the adopted learning outcomes and student workload in relation to the number of ECTS credits allocated to activities and courses as a whole).

Overview of course assesment

Learning outcomes
Upon successful completion of the course, students will be able to:

1. create a computer programme which uses the Hough transformation and RANSAC algorithm for solving computer vision problems

2. create a computer programme for recognition of 2D and 3D objects in an image acquired by a standard and 3D camera

3. to perform the calibration of a camera and a stereo camera system

4. combine programme components for creating 3D models of objects and scenes from two or multiple images acquired by a standard and 3D camera into a computer application

5. to explain how a mobile robot can localize itself in an operating environment using computer vision

6. create a computer program which implements basic computer vision methods using appropriate program libraries for computer vision



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