Bachelor
Informatica
Informatiekunde
Kunstmatige intelligentie
Master
Computing Science
Game&Media Technology
Artifical Intelligence
Business Informatics

Website: | website containing additional information | ||||||||||||||||||||||

Course code: | INFOMAGR | ||||||||||||||||||||||

Credits: | 7.5 ECTS | ||||||||||||||||||||||

Period: | period 2 (week 46 through 5, i.e., 10-11-2014 through 30-1-2015; retake week 11)
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Timeslot: | A | ||||||||||||||||||||||

Participants: | up till now 25 subscriptions | ||||||||||||||||||||||

Schedule: | Official schedule representation can be found in Osiris | ||||||||||||||||||||||

Teachers: | Dit is een oud rooster!
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Exam: |
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Contents: | ADVANCED GRAPHICS 2014/2015.The master course Advanced Graphics addresses advanced topics in 3D computer graphics. The focus of the course is physically-based rendering of 3D scenes. The course has three main focus areas: Mathematical and physical fundamentals, rendering algorithms, and methods for increasing efficiency. The lecture starts by introducing the physical model of light transport: Ray optics, the equilibrium conditions for light transport ("Rendering Equation"), etc. In order to understand this notion more precisely, we will then look at the mathematical tools from calculus and linear algebra that are necessary to capture the intuitive model in a rigorous mathematical formalism. Afterwards, the lecture discusses several basic rendering algorithms (finite element radiosity/radiance, path tracing, photon tracing, and discusses standard optimizations (basis functions, variance reduction). The last part deals with efficiency, focusing on Monte-Carlo algorithms for a fast, output-sensitive approximation of the solution of the rendering equation. The lecture will include a short recap on fundamental concepts from probability theory required to understand the properties and design choices of these algorithms. Prerequisites:
This course is rather heavy in mathematics and formal methods. Although the lecture will emphasize on intuition, the students will often need to take an abstract/structural point of view to understand the material. Further, a strong programming background is required. Detailed prerequisites:(i) Basic knowledge in linear algebra, calculus, probability theory as required for the masters program ("elementary maths for GMT"). The course will go beyond the elementary concepts, so plan for enough time to work on this during the course.(ii) Fundamentals in algorithms and data structures. Bachelor level knowledge in computer graphics is recommended.(iii) Good programming skills; C++ recommended (you can use other languages at your own risk). Plan for additional time if you plan to familiarize yourself with C++ during the course.(iv) Good to have: Basic experience with graphics APIs (such as OpenGL). Plan for additional time if you need to acquire the skills during the course. | ||||||||||||||||||||||

Literature: | The course does not strictly follow a fixed textbook. However, the following book discusses all topics of the course, but in greater depth than what can be handled in one period. The lecture will therefore deviate from the textbook in terms of depth and, for simplicity, also in notation. Nonetheless, it is a good supplementary read, and highly recommended:Andrew Glassner: Principles of Digital Image Synthesis. CC-online version at: www.realtimerendering.com/Principles_of_Digital_Image_Synthesis_v1.0.1.pdf Additional literature will be posted on the course web site. | ||||||||||||||||||||||

Course form: | The course consists of a lecture and a practical project. The lecture will take place in the first two month (Nov+Dec) of the period, the practical part will be held in the last month (Jan). The course will have three sessions à 90 min. per week (Mo,Tue,We). In addition, there will be regular homeworks discussed in an additional session. Homework will be graded through group interviews. | ||||||||||||||||||||||

Exam form: | In order to pass the course, there are four requirements:(i) The students must work on all homework assignments and achieve a grade of at least 5.0 before rounding. See the course web page for detailed homework rules and grading procedure.(ii) The students must successfully complete the practical project, at least graded with 5.0. The project will be done as group work, see course web page for details.(iii) The students must participate in a final exam. The minimum grade required in the final exam is also 5.0.(iv) The overall score is a weighted average of homework (17%), practicals (33%), and final exam (50%). The overall score must be at least 6.0 after rounding to pass the course. | ||||||||||||||||||||||

Minimum effort to qualify for 2nd chance exam: | A grade of at least 4.0 is required in all three areas (homework, final exam, practicals). This allows the student to participate in a retake exam. The result of the retake exam will be weighted by 50% and the original overall course score also by 50%. If the new grade resulting from this average is better than the original one, it will replace the original grade. Otherwise, the retake exam has no effect. A retake of a part is not possible if the grade is at least 6.0 or less than 4.0. (see website for details). |