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所在平台: Coursera专项课程 |
课程主页: https://www.coursera.org/specializations/firstprinciplesofcomputervision
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课程名称：计算机视觉的第一原理 课程概述： 本课程旨在使学习者掌握数字相机的工作原理，以及图像处理的基础知识。学习者将会创建特征检测理论，并开发从图像中提取特征的算法。此外，课程将探索利用视觉线索（如阴影、失焦等）从多个图像或视角恢复物体的三维形状的新方法。课程还将涉及图像分割、物体跟踪和物体识别等基本感知任务。 获得的技能： - 感知 - 特征与边界 - 物体识别 - 相机与成像 - 三维重建 - 傅里叶变换 - 高动态范围（HDR）成像 - 图像形成 - 卷积与反卷积 - 相机工作原理 - 规模空间 - 有效轮廓 关于本专业化： 这个专业化课程是对计算机视觉基础的全面阐述，侧重于视觉的数学和物理基础，旨在为对计算机视觉几乎没有知识的学习者、从业者和研究人员提供教育。课程包含五个系列课程。完成本专业化的学习者有望在计算机视觉这一快速发展的领域中建立成功的职业生涯，该领域预计在未来几十年将日益重要。 应用学习项目： 学习者将通过应用模型和工具，包括图像处理、图像特征、构建三维场景、图像分割和物体识别，来发展对计算机视觉的基础知识。该专业化课程还包括约250道评估题。对计算机视觉基础知识的掌握在众多技术公司和研究机构中被高度重视。 认证： 完成课程后将获得可分享的证书。 学习形式： - 100% 在线课程 - 灵活的学习时间表 - 建议学习时间：每周2小时，预计7个月完成 - 初学者水平，需具备基础的线性代数和微积分知识，了解任意编程语言将有助于学习，但不是必要条件。 如需了解更多信息，可访问课程链接：[计算机视觉的第一原理](https://www.coursera.org/learn/cameraandimaging)。
Course Link: https://www.coursera.org/learn/cameraandimaging
Name:Camera and Imaging
Description:Offered by Columbia University. This course covers the fundamentals of imaging – the creation of an image that is ready for consumption or ... Enroll for free.
Course Link: https://www.coursera.org/learn/features-and-boundaries
Name:Features and Boundaries
Description:Offered by Columbia University. This course focuses on the detection of features and boundaries in images. Feature and boundary detection is ... Enroll for free.
Course Link: https://www.coursera.org/learn/3d-reconstruction---single-viewpoint
Name:3D Reconstruction - Single Viewpoint
Description:Offered by Columbia University. This course focuses on the recovery of the 3D structure of a scene from its 2D images. In particular, we are ... Enroll for free.
Course Link: https://www.coursera.org/learn/3d-reconstruction-multiple-viewpoints
Name:3D Reconstruction - Multiple Viewpoints
Description:Offered by Columbia University. This course focuses on the recovery of the 3D structure of a scene from images taken from different ... Enroll for free.
Course Link: https://www.coursera.org/learn/perception
Name:Visual Perception
Description:Offered by Columbia University. The ultimate goal of a computer vision system is to generate a detailed symbolic description of each image ... Enroll for free.
What you will learn
Master the working principles of a digital camera and learn the fundamentals of imaging processing
Create a theory of feature detection and develop algorithms for extracting features from images
Explore novel methods for using visual cues (shading, defocus, etc.) to recover the 3D shape of an object from multiple images or viewpoints
Get exposed to fundamental perceptions tasks such as image segmentation, object tracking, and object recognition
Skills you will gain
perception
features and boundaries
Object Recognition
Camera and imaging
3d reconstruction
Fourier Transform
High-Dynamic-Range (HDR) Imaging
Image Formation
Convolution and Deconvolution
Working Principles of a Camera
Scale Space
Active Contours
About this Specialization
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This specialization presents the first comprehensive treatment of the foundations of computer vision. It focuses on the mathematical and physical underpinnings of vision and has been designed for learners, practitioners and researchers who have little or no knowledge of computer vision. The program includes a series of 5 courses. Any learner who completes this specialization has the potential to build a successful career in computer vision, a thriving field that is expected to increase in importance in the coming decades.
Applied Learning Project
Learners will develop the fundamental knowledge of computer vision by applying the models and tools including: image processing, image features, constructing 3D scene, image segmentation and object recognition. The specialization includes roughly 250 assessment questions. Proficiency in the fundamentals of computer vision is valued by a wide range of technology companies and research organizations.
Shareable Certificate
Shareable Certificate
Earn a Certificate upon completion
100% online courses
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Flexible Schedule
Set and maintain flexible deadlines.
Beginner Level
Beginner Level
Learners should know the fundamentals of linear algebra and calculus. Knowing any programming language is beneficial, but not required.
Hours to complete
Approximately 7 months to complete
Suggested pace of 2 hours/week
Available languages
English
Subtitles: English
Shareable Certificate
Shareable Certificate
Earn a Certificate upon completion
100% online courses
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Flexible Schedule
Set and maintain flexible deadlines.
Beginner Level
Beginner Level
Learners should know the fundamentals of linear algebra and calculus. Knowing any programming language is beneficial, but not required.
Hours to complete
Approximately 7 months to complete
Suggested pace of 2 hours/week
Available languages
English
Subtitles: English
