24 monthsProgramme duration
13,315 USDTuition Fee/year
Programme overview
Main Subject
Mathematics
Degree
Other
Study Level
Masters
Study Mode
Blended
Visual computing is an emerging field that combines computer graphics, computer vision and virtual reality to advance cutting-edge methodologies for the acquisition, processing, manipulation and rendering of visual content. This multidisciplinary program is designed to provide students with the knowledge and technological skills to understand and develop sophisticated problem solutions in innovative-driven industries such as entertainment, medicine, robotics, criminology and security, Computer Aided Design (CAD) or machine vision.
This program enables scientists and engineers in the areas of computer vision and computer graphics (CG) to expand their skills in the application of both traditional and cutting-edge techniques. Topics include computer vision (image representation, filtering, classification, segmentation, feature detection, motion estimation, etc.), CG imaging (light, colors, shading, ray tracing, texture mapping, bump mapping, anti-aliasing, etc.), CG modeling (parametric and implicit curves and surfaces, meshes, point clouds, etc.), CG animation (shape and motion modeling, rigid bodies, deformable objects, fluids, interactive dynamic animations, etc.). The program also covers visual computing mathematics (e.g. discrete and continuous differential geometry of curves and surfaces and geometry processing on meshes), deep learning for computer vision (e.g. using machine learning for object detection and recognition, convolutional neural networks, recurrent neural networks, supervised and unsupervised learning, and deep neural generative models for 3D geometry), and interactive CG (e.g. virtual objects, images, worlds, and environments, immersive vs non-immersive VR, 3D interface design).
This program enables scientists and engineers in the areas of computer vision and computer graphics (CG) to expand their skills in the application of both traditional and cutting-edge techniques. Topics include computer vision (image representation, filtering, classification, segmentation, feature detection, motion estimation, etc.), CG imaging (light, colors, shading, ray tracing, texture mapping, bump mapping, anti-aliasing, etc.), CG modeling (parametric and implicit curves and surfaces, meshes, point clouds, etc.), CG animation (shape and motion modeling, rigid bodies, deformable objects, fluids, interactive dynamic animations, etc.). The program also covers visual computing mathematics (e.g. discrete and continuous differential geometry of curves and surfaces and geometry processing on meshes), deep learning for computer vision (e.g. using machine learning for object detection and recognition, convolutional neural networks, recurrent neural networks, supervised and unsupervised learning, and deep neural generative models for 3D geometry), and interactive CG (e.g. virtual objects, images, worlds, and environments, immersive vs non-immersive VR, 3D interface design).
Programme overview
Main Subject
Mathematics
Degree
Other
Study Level
Masters
Study Mode
Blended
Visual computing is an emerging field that combines computer graphics, computer vision and virtual reality to advance cutting-edge methodologies for the acquisition, processing, manipulation and rendering of visual content. This multidisciplinary program is designed to provide students with the knowledge and technological skills to understand and develop sophisticated problem solutions in innovative-driven industries such as entertainment, medicine, robotics, criminology and security, Computer Aided Design (CAD) or machine vision.
This program enables scientists and engineers in the areas of computer vision and computer graphics (CG) to expand their skills in the application of both traditional and cutting-edge techniques. Topics include computer vision (image representation, filtering, classification, segmentation, feature detection, motion estimation, etc.), CG imaging (light, colors, shading, ray tracing, texture mapping, bump mapping, anti-aliasing, etc.), CG modeling (parametric and implicit curves and surfaces, meshes, point clouds, etc.), CG animation (shape and motion modeling, rigid bodies, deformable objects, fluids, interactive dynamic animations, etc.). The program also covers visual computing mathematics (e.g. discrete and continuous differential geometry of curves and surfaces and geometry processing on meshes), deep learning for computer vision (e.g. using machine learning for object detection and recognition, convolutional neural networks, recurrent neural networks, supervised and unsupervised learning, and deep neural generative models for 3D geometry), and interactive CG (e.g. virtual objects, images, worlds, and environments, immersive vs non-immersive VR, 3D interface design).
This program enables scientists and engineers in the areas of computer vision and computer graphics (CG) to expand their skills in the application of both traditional and cutting-edge techniques. Topics include computer vision (image representation, filtering, classification, segmentation, feature detection, motion estimation, etc.), CG imaging (light, colors, shading, ray tracing, texture mapping, bump mapping, anti-aliasing, etc.), CG modeling (parametric and implicit curves and surfaces, meshes, point clouds, etc.), CG animation (shape and motion modeling, rigid bodies, deformable objects, fluids, interactive dynamic animations, etc.). The program also covers visual computing mathematics (e.g. discrete and continuous differential geometry of curves and surfaces and geometry processing on meshes), deep learning for computer vision (e.g. using machine learning for object detection and recognition, convolutional neural networks, recurrent neural networks, supervised and unsupervised learning, and deep neural generative models for 3D geometry), and interactive CG (e.g. virtual objects, images, worlds, and environments, immersive vs non-immersive VR, 3D interface design).
Admission Requirements
105+
2.5+
6+
70+
- A Bachelor’s degree in Computer Science, Computer Engineering, Mathematics, or a related quantitative field.
- Grades of at least B (or equivalent) in most Mathematics and Statistics courses.
- Required preparatory courses include undergraduate courses in calculus, linear algebra, probability and statistics, differential equations, numerical methods, and programming.
- Demonstrated high-level proficiency in programming (e.g., Python, C++, or Java). Note: Due to the intensive nature of the projects, a strong programming background is essential for success.
- The admission process goes beyond meeting the minimum requirements.
- The list of courses, offered at KFUPM, which are equivalent to the required preparatory undergraduate instruction in calculus, linear algebra, probability and statistics, differential equations, numerical methods, and programming are given below for each program: Math 101, Math 102, Math 201, Math 202, Math 225, Math 333, Math 371, Stat 201, 212, 214 or 319 ICS 104
2 Years
- Candidates are required to submit references or letter(s) of recommendation for acceptance
- Candidates are required to submit an essay(s) for acceptance
Tuition fees
Domestic
13,315 USD
International
13,315 USD
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