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Machine Vision

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:

Required Literature

No.

Author

Title

Publisher

Year

1

Richard Szelisk

Computer Vision: Algorithms and Applications

Springer London

2011

Additional Literature

No.

Author

Title

Publisher

Year

1

Richard Hrtley, Andrew Zisserman

Multiple View Geometry in Computer Vision

Cambridge University Press

2003