Visual computing is an emerging discipline that combines computer vision, deep learning, computer graphics, and interactive techniques to advance technologies for the acquisition, analysis, manipulation, and creation of 2D or 3D visual content. This concentration of the professional master's program trains computer vision scientists, software engineers, and computer graphics experts in the application of cutting-edge deep learning techniques as well as traditional methods and technologies. Graduates contribute their expertise to industries specializing in computer vision, deep learning, robotics, visual effects, video games, autonomous driving, medical imaging, or companies dealing with visual data analysis and manipulation, including social media and video-sharing platforms.

CURRICULUM

The current curriculum of the visual computing concentration covers (but is not limited to) the following topics:

  • Fundamentals and advanced knowledge related to computer vision, computer graphics, and image processing.
  • Machine learning, deep learning, and data-driven techniques in visual computing.
  • Geometric, procedural, and physics-based modelling in computer graphics and computer animation.
  • Pattern and action recognition in images and video.
  • Visual data acquisition, e.g. computational photography, laser scanning, and geometry and motion tracking.
  • Human-computer interfaces and interactive techniques for visual computing.
  • Fundamentals and advanced technologies in augmented/mixed/virtual reality.
  • Visual computing on specialized data and applications, e.g. medical, simulation, AR/VR, 3D games, and robotics, etc.
  • Computational design and fabrication, e.g. 3D printing.

COURSE WORK

The layout below shows the recommended course options. For the full list of course options, please see the official calendar entry for the Professional Master of Science in Computer Science.

CORE COURSES (12 CREDITS)

All students complete the required core courses as laid out below:

  • CMPT 726 Machine Learning
  • CMPT 756 Distributed and Cloud Systems

At least two of:

  • CMPT 757 Frontiers of Visual Computing
  • CMPT 762 Computer Vision
  • CMPT 764 Geometric Modelling in Computer Graphics
  • CMPT 766 Computer Animation and Simulation
  • CMPT 767 Visualization
  • CMPT 820 Multimedia Systems
  • CMPT 822 Computational Vision  

LAB COURSES (12 CREDITS)

The mandatory lab courses provide hands-on learning of various models, algorithms, and software related to visual computing. Students will take the following two lab courses for 6 credits each.  Only students enrolled in the visual computing concentration are permitted to register in these courses:

  • CMPT 742 Practices for Visual Computing 1
  • CMPT 743 Practices for Visual Computing 2

ELECTIVE Courses (3 CREDITS)

Students must complete one elective (typically 3 credits) from the following list of courses:

  • CMPT 727 Statistical Machine Learning
  • CMPT 728 Deep Learning
  • CMPT 729 Reinforcement learning
  • CMPT 763 Biomedical Computer Vision
  • CMNS 815 Communication Theories in Technology and Society
  • A special topics course in Computing Science:  CMPT 829, 886, 889, 980, 981, 982, 983, 984, 985
  • Other courses with permission of the School

Course outlines for SFU's Computing Science courses can be found here. For all other outlines, please go here.

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