Course: Machine Vision
Code: 3ФЕИТ05009
ECTS points: 6 ECTS
Number of classes per week: 3+0+0+3
Lecturer: Prof. Dr. Zoran Ivanovski
Course Goals (acquired competencies): The goal of this course is to enable students to acquire broad knowledge about the theoretical and practical aspects of image analysis and machine vision. Upon successful completion of the course the student will understand the theoretical bases, algorithms and performance of robust feature detection, different registration methods, image alignment and matching, bases of 2D and 3D machine vision and scene and objects categorization. They will acquire practical skills required for research, development and implementation of machine vision applications.
Course Syllabus: Basic concepts and definitions of scene, image, image processing and machine vision. Image segmentation. Image representation and description. Context recognition. Image search and retrieval. Automated image annotation. Object description and recognition. Human figure and face recognition. Feature tracking and motion estimation. Image formation models. Single and multiple view 3D scene reconstruction. Structure from motion. Structure from focus, silhouettes and shadows.
Literature:
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Required Literature |
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No. |
Author |
Title |
Publisher |
Year |
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1 |
Richard Szelisk | Computer Vision: Algorithms and Applications | Springer London | 2011 |
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Additional Literature |
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No. |
Author |
Title |
Publisher |
Year |
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1 |
Richard Hrtley, Andrew Zisserman | Multiple View Geometry in Computer Vision | Cambridge University Press | 2003 |
