Computer Graphics and Scientific Computing Thomas Sangild Sørensen.

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Computer Graphics and Scientific Computing Thomas Sangild Sørensen

Transcript of Computer Graphics and Scientific Computing Thomas Sangild Sørensen.

Computer Graphics and Scientific Computing

Thomas Sangild Sørensen

Course overview

• Department of Computer Science– Introduction to computer graphics and image

processing (Q1)

– Data-parallel computing (Q1)

– Advanced image processing (Q2)

– Advanced real-time graphics effects (Q2)

Dependencies

Q1

Q2

Contents

• Data-parallel computing– “programming massively parallel systems”

– The data-parallel programming language CUDA – Data-parallel concepts and algorithms – Examples and performance considerations of

data-parallel applications

Contents

• Introduction to Computer Graphics and Image Processing– Rendering using the conventional graphics

pipeline and OpenGL – Data structures for graphics – Linear operators for image processing

(convolution, Fourier transform, filtering) – Accumulative project implementation

Contents• Advanced real-time graphics effects– Graphics effects for modern games, e.g.• screen space effects for shadows • color reflections • anti aliasing

Contents• Advanced Image Processing– E.g. image reconstruction, filtering, segmentation,

and registration from• variational calculus • partial differential equations • solving linear and non-linear systems of equations

Example of “image deconvolution”.Top hit on Google images, from the Hubble space telescope

Transition period Q&A

• I already passed Peter Møller-Nielsens course on introductory computer graphics, but would like to join the advanced image processing course– Should I sign up for the course “introduction to

computer graphics and image processing”?– Yes. And you will be given an extra mandatory

assignment to replace the to computer graphics contents with image processing material

Signal Proceesing and Computer Vision @ Aarhus School of Engineering

Master Courses Q3/Q4 (5 ECTS)• Advanced Signal Processing and Analysis (Q3)• Non-linear Signal Processing and Pattern Recognition

(Q3)• Computer Vision (Q4)

More info: • Contact Ingeniørdocent Henrik Karstoft, ASE,

e-mail: [email protected]• For details on these courses see:

http://www.iha.dk/Kursuskatalog-5044.aspx

Henrik Karstoft ([email protected])

Aarhus School of Engineering

In conclusion

• A good selection of courses for specialization in computer vision, imaging and graphics

• Questions?– Come see me outside or contact me by email:– [email protected]