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 AD4M33TZ Theoretical foundations of computer vision, graphics, and interaction Extent of teaching: 14+6c Guarantors: Roles: PO,V Language ofteaching: CS Teachers: Completion: Z,ZK Responsible Department: 13133 Credits: 6 Semester: L

Anotation:

We will explain fundamentals of image and space geometry including Euclidean, affine and projective geometry, the model of a perspective camera, image transformations induced by camera motion, and image normalization for object recognition. Then we will study methods of calculating geometrical objects in images and space, estimating geometrical models from observed data, and for calculating geometric and physical properties of observed objects. The theory will be demonstrated on practical task of creating mosaics from images, measuring the geometry of objects by a camera, and reconstructing geometrical and physical properties of objects from their projections. We will build on linear algebra, probability theory, numerical mathematics and optimization and lay down foundation for other subjects such as computational geometry, computer vision, computer graphics, digital image processing and recognition of objects in images.

Study targets:

The goal is to present the theoretical background for modeling of perspective cameras and solving tasks of measurement in images and scene reconstruction.

Course outlines:

 1 Computer vision, graphics, and interaction - the discipline and the subject. 2 Modeling world geometry in the affine space. 3 The mathematical model of the perspective camera. 4 Relationship between images of the world observed by a moving camera. 5 Estimation of geometrical models from image data. 6 Optimal approximation using points and lines in L2 and minimax metric. 7 The projective plane. 8 The projective, affine and Euclidean space. 9 Transformation of the projective space. Invariance and covariance. 10 Random numbers and their generating. 11 Randomized estimation of models from data. 12 Construction of geometric objects from points and planes using linear programming. 13 Calculation of spatial object properties using Monte Carlo simulation. 14 Review.

Exercises outline:

1Introduction, a-test 2-4Linear algebra and optimization tools for computing with geometrical objects 5-6Cameras in affine space - assignment I 7-8Geometry of objects and cameras in projective space - assignment II 9-10Principles of randomized algorithms - assignment III. 11-14Randomized algorithms for computing scene geometry - assignment IV.

Literature:

 [1] P. Ptak. Introduction to Linear Algebra. Vydavatelstvi CVUT, Praha, 2007. [2] E. Krajnik. Maticovy pocet. Skriptum. Vydavatelstvi CVUT, Praha, 2000. [3] R. Hartley, A.Zisserman. Multiple View Geometry in Computer Vision.
Cambridge University Press, 2000.
 [4] M. Mortenson. Mathematics for Computer Graphics Applications. Industrial Press. 1999

Requirements:

A standard course in Linear Algebra.

Keywords:

Computer vision and graphics, Euclidean, affine, projective geometry, perspective camera, random numbers, randomized algorithms, Monte Carlo simulation, linear programming.

Subject is included into these academic programs:

 Program Branch Role Recommended semester MKEEM1 Technological Systems V 2 MKEEM5 Economy and Management of Electrical Engineering V 2 MKEEM4 Economy and Management of Power Engineering V 2 MKEEM3 Electrical Power Engineering V 2 MKEEM2 Electrical Machines, Apparatus and Drives V 2 MKOI4 Computer Graphics and Interaction PO 2 MKKME1 Wireless Communication V 2 MKKME5 Systems of Communication V 2 MKKME4 Networks of Electronic Communication V 2 MKKME3 Electronics V 2 MKKME2 Multimedia Technology V 2 MKOI3 Computer Vision and Image Processing PO 2 MKKYR4 Aerospace Systems V 2 MKKYR1 Robotics V 2 MKKYR3 Systems and Control V 2 MKKYR2 Sensors and Instrumentation V 2

 Page updated 17.6.2019 09:52:48, semester: Z,L/2020-1, L/2018-9, Z,L/2019-20, Send comments about the content to the Administrators of the Academic Programs Proposal and Realization: I. Halaška (K336), J. Novák (K336)