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Added CMU 462 Computer Graphics (#209)

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Added a great course on Computer Graphics offered by Carnegie Mellon
University
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@ -761,6 +761,10 @@ and anti-analysis techniques.
- An introductory course in computer vision and computational photography focusing on four topics: image features, image morphing, shape matching, and image search.
- [Lectures](https://alliance.seas.upenn.edu/~cis581/wiki/index.php?title=Schedule)
- [Assignments](https://alliance.seas.upenn.edu/~cis581/wiki/index.php?title=Projects)
- [CMU 462](http://15462.courses.cs.cmu.edu/fall2015) **Computer Graphics** *Carnegie Mellon University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- This course provides a comprehensive introduction to computer graphics. Focuses on fundamental concepts and techniques, and their cross-cutting relationship to multiple problem domains in graphics (rendering, animation, geometry, imaging). Topics include: sampling, aliasing, interpolation, rasterization, geometric transformations, parameterization, visibility, compositing, filtering, convolution, curves & surfaces, geometric data structures, subdivision, meshing, spatial hierarchies, ray tracing, radiometry, reflectance, light fields, geometric optics, Monte Carlo rendering, importance sampling, camera models, high-performance ray tracing, differential equations, time integration, numerical differentiation, physically-based animation, optimization, numerical linear algebra, inverse kinematics, Fourier methods, data fitting, example-based synthesis.
- [Lectures and Readings](http://15462.courses.cs.cmu.edu/fall2015/reading)
- [Assignments and Quizes](http://15462.courses.cs.cmu.edu/fall2015/exercises)
- [CS 378](https://github.com/ut-cs378-vision-2014fall/course-info) **3D Reconstruction with Computer Vision** *UTexas* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- In this lab-based class, we'll dive into practical applications of 3D reconstruction, combining hardware and software to build our own 3D environments from scratch. We'll use open-source frameworks like OpenCV to do the heavy lifting, with the focus on understanding and applying state-of-the art approaches to geometric computer vision
- [Lectures](https://github.com/ut-cs378-vision-2014fall/course-info/tree/master/meeting-notes)