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Computer Graphics and Scientific Computing

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).

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Computer Graphics and Scientific Computing

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  1. Computer Graphics and Scientific Computing Thomas Sangild Sørensen

  2. 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)

  3. Dependencies Q1 Q2

  4. 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

  5. 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

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

  7. 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

  8. 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

  9. Signal Proceesing and Computer Vision @ Aarhus School of Engineering Henrik Karstoft (hka@iha.dk) 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: hka@iha.dk For detailson thesecoursessee: http://www.iha.dk/Kursuskatalog-5044.aspx

  10. 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: • sangild@cs.au.dk

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