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This course will introduce the audience to the subject of computer vision. The camera model will be introduced and camera calibration and epipolar geometry concepts will be explained. Object and texture representation will be discussed, and effect of light and shading and colour will be introduced. Use of CNN in vision will be taught, especially for object detection/classification and depth estimation.
INTENDED AUDIENCE: Any Interested LearnersPREREQUISITES:
1. Basic calculus: Finding derivatives, maximize a function by finding where the derivative=0.2. Linear algebra: Matrix transpose, inverse, and other operations to do algebra with matrix expressions. Transformation matrices to rotate/transform points, Singular Value Decomposition. 3. Basic probability and statistics: Understanding of conditional probability, mean, and variance.
4. Some programming skills: such as entry-level Matlab/python and the ability to work in the Linux environment
INDUSTRY SUPPORT: Samsung, Qualcomm, LG, TI, Google, Microsoft, amazon, Facebook and many more
INTENDED AUDIENCE: Any Interested LearnersPREREQUISITES:
1. Basic calculus: Finding derivatives, maximize a function by finding where the derivative=0.2. Linear algebra: Matrix transpose, inverse, and other operations to do algebra with matrix expressions. Transformation matrices to rotate/transform points, Singular Value Decomposition. 3. Basic probability and statistics: Understanding of conditional probability, mean, and variance.
4. Some programming skills: such as entry-level Matlab/python and the ability to work in the Linux environment
INDUSTRY SUPPORT: Samsung, Qualcomm, LG, TI, Google, Microsoft, amazon, Facebook and many more