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.
提供方
纽约州立大学布法罗分校
纽约州立大学纽约州立大学
Computer Vision Basics
纽约州立大学布法罗分校課程信息
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中級
Basic programming skills & experience; familiarity with basic linear algebra, calculus & probability, and 3D co-ordinate systems & transformations
完成時間大約為10 小時
英語（English）
字幕：英語（English）
您將學到的內容有
Understand what computer vision is and its goals
Identify some of the key application areas of computer vision
Understand the digital imaging process
Apply mathematical techniques to complete computer vision tasks
您將獲得的技能
Computer VisionComputer ProgrammingMatlab
可分享的證書
完成後獲得證書
100% 在線
立即開始，按照自己的計劃學習。
可靈活調整截止日期
根據您的日程表重置截止日期。
中級
Basic programming skills & experience; familiarity with basic linear algebra, calculus & probability, and 3D co-ordinate systems & transformations
完成時間大約為10 小時
英語（English）
字幕：英語（English）
提供方
纽约州立大学布法罗分校
The University at Buffalo (UB) is a premier, research-intensive public university and the largest, most comprehensive institution of the State University of New York (SUNY) system. UB offers more than 100 undergraduate degrees and nearly 300 graduate and professional programs.
纽约州立大学纽约州立大学
The State University of New York, with 64 unique institutions, is the largest comprehensive system of higher education in the United States. Educating nearly 468,000 students in more than 7,500 degree and certificate programs both on campus and online, SUNY has nearly 3 million alumni around the globe.
教學大綱 - 您將從這門課程中學到什麼
完成時間為 3 小時
Computer Vision Overview
In this module, we will discuss what computer vision is, the fields related to it, the history and key milestones of it, and some of its applications.
完成時間為 3 小時
13 個視頻 （總計 42 分鐘）, 2 個閱讀材料, 4 個測驗
13 個視頻
Meet Jungsong Yuan, Ph.D.24
What is Computer Vision?6分鐘
Why Computer Vision?40
Related Fields of Computer Vision4分鐘
Relevant Fields56
Computer Programming & Computer Vision1分鐘
Computer Vision Awareness1分鐘
Timelines & Milestones8分鐘
Computer Vision Progression1分鐘
Computer Vision Applications8分鐘
CV Applications4分鐘
CV Impact in the Field of Augmented Reality1分鐘
2 個閱讀材料
Resources (Optional): Computer Vision Overview30分鐘
REQUIRED - MATLAB Resources10分鐘
3 個練習
What is Computer Vision?2分鐘
Related Fields of Computer Vision2分鐘
MATLAB Basics5分鐘
完成時間為 3 小時
Color, Light, & Image Formation
In this module, we will discuss color, light sources, pinhole and digital cameras, and image formation.
完成時間為 3 小時
4 個視頻 （總計 32 分鐘）, 1 個閱讀材料, 5 個測驗
1 個閱讀材料
Resources (Optional): Color, Light, & Image Formation30分鐘
3 個練習
Light Sources4分鐘
Pinhole Camera Model2分鐘
Digital Camera2分鐘
完成時間為 2 小時
Low-, Mid- & High-Level Vision
In this module, we will discuss the three-level paradigm of computer vision that was proposed by David Marr. We will also discuss low, mid, and high level vision.
完成時間為 2 小時
5 個視頻 （總計 32 分鐘）, 1 個閱讀材料, 3 個測驗
5 個視頻
Low-, Mid-, High-Level Vision1分鐘
Low-Level Vision8分鐘
Mid-Level Vision7分鐘
High-Level Vision6分鐘
1 個閱讀材料
Resources (Optional): Low-, Mid- and High-Level Vision30分鐘
2 個練習
Three-Level Paradigm2分鐘
Low-Level Vision2分鐘
完成時間為 2 小時
Mathematics for Computer Vision
In this lecture, we will discuss the Mathematics used in Computer Vision, which includes linear algebra, calculus, probability, and much more.
完成時間為 2 小時
8 個視頻 （總計 10 分鐘）, 2 個閱讀材料, 2 個測驗
8 個視頻
Mathematical Preliminaries27
Linear Algebra1分鐘
Calculus45
Probability Theory35
Algorithms38
Using Algorithms1分鐘
Aligning RGB channels2分鐘
2 個閱讀材料
Resources (Optional): Mathematics for Computer Vision30分鐘
Computer Vision Basics - Key Takeaways10分鐘
1 個練習
Algorithms2分鐘
審閱
來自COMPUTER VISION BASICS的熱門評論
由 LM 提供2019年8月10日
It is a good introduction course but I think some more demo coding for matlab in the first assignments will be a good thing so we don´t have to spend a lot of time on google and on trial and error.
由 PS 提供2019年10月12日
Course was great ! And explained well but Matlab was not explained well. It's hard to complete week-4 assignment if you are not good at Matlab. Please provide python language for solving problems.
由 PW 提供2020年5月22日
The course is fine, but it's too fundamental. Overall, it is more suit to personal who already had the fundamental in image processing knowledge. Else the course is a but higher level for others.
由 AO 提供2020年4月28日
Lays a good foundation for Computer Vision. There should be more programming examples as some of the labs were beyond the scope of what was taught in the videos, especially the last one.
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Are there any prerequisites?
Learners should have basic programming skills and experience (understanding of for loops, if/else statements). Learners should also be familiar with the following: basic linear algebra (matrix vector operations and notation), 3D co-ordinate systems and transformations, basic calculus (derivatives and integration), basic probability (random variables), and 3D co-ordinate systems & transformations.
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