Introduction to Computer Vision (Full Course)

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By the end of this course, learners will understand what computer vision is, as well as its mission of making computers see and interpret the world as humans do, by learning core concepts of the field and receiving an introduction to human vision capabilities. They are equipped to identify some key application areas of computer vision and understand the digital imaging process. The course covers crucial elements that enable computer vision: digital signal processing, neuroscience and artificial intelligence. Topics include color, light and image formation; early, mid- and high-level vision; and mathematics essential for computer vision. Learners will be able to apply mathematical techniques to complete computer vision tasks.

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👉COMPUTER VISION OVERVIEW
0:00:00 What is Computer Vision
0:07:18 Related fields of Computer Vision
0:16:07 Timelines Milestone
0:25:41 Computer Vision Applications

👉COLOR LIGHT IMAGE FORMATION
0:40:47 Light Sources
0:49:31 Pinhole Camera Model
0:58:35 Digital Camera
1:04:29 Color Theory

👉LOW MID HIGH LEVEL VISION
1:13:00 Three level paradigm
1:22:44 Low level vision
1:31:21 Mid level vision
1:38:35 High Level vision

👉MATHEMATICS FOR COMPUTER VISION
1:45:26 Mathematical preliminaries
1:48:01 Linear Algebra
1:49:41 Calculus
1:50:27 Probability Theory
1:51:03 Algorithms
1:53:21 Mathematics for Computer vision resources and evaluation

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