NOTE: this course is discontinued as of 2016 and is replaced by 5SH0!
As an introduction, learn theory and practice of the newest advanced video compression standards, like wavelets in JPEG2000, and MPEG-4/H.264. The main part of the course is about video content analysis.
Learn theoretical and practical knowledge of multimedia video coding systems with respect to basic techniques, coding standards like MPEG/JPEG and architectures for implementation.
Learn theoretical and practical knowledge of multimedia video coding systems with respect to basic techniques, coding standards like MPEG/JPEG and architectures for implementation.
Learn the theory and algorithms of video signal analysis, and finding features and objects in image/video. Learn the basics of 3D image processing, sensing in 3D and 3D model reconstruction. Learn the practical basics of MATLAB programming and analysis and/or 3D algorithms for practical applications in surveillance and medical imaging.
Learn the theory and algorithms of video signal analysis, and finding features and objects in image/video. Learn the basics of 3D image processing, sensing in 3D and 3D model reconstruction. Learn the practical basics of MATLAB programming and analysis and/or 3D algorithms for practical applications in surveillance and medical imaging and learn the basics of deep learning.
Goal
Become acquainted with the implementation of image filtering in the spatial and frequency domain, the application of image restoration and color image processing algorithms, finding image attributes (points, edges, etc.) and features, controlling segmentation parameters for obtaining optimal results and gain a basic understanding of machine learning algorithms and their validation.
Goal
Become acquainted with the theory and main concepts of digital signal and analysis; make a choice of an approach for a given basic signal/image processing problem; implement the chosen approach in MATLAB and critically evaluate the result; be able to operationalize theoretical concepts from signal/image analysis in a hands-on case study.
WIC Midwintermeeting on Deep Learning TU Eindhoven, Zwarte Doos (Filmzaal), January 24, 2018.
The werkgemeenschap Information and Communication theory organizes annually a one-day meeting with tutorial lectures and new work on an actual technical theme. This year the theme is Deep Learning, which is revolutionizing areas in computer vision, signal processing and machine learning.
