Online Course – Certified Professional Internship in First Principles of Computer Vision – Google, Columbia University

Master the main principles of computer vision. Advance the mathematical and physical algorithms that drive the field of computer vision.

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קורס אונליין - התמחות מקצועית מוסמכת בעקרונות ראשוניים של ראיה ממוחשבת - גוגל

Professional Certificate

Beginners

No prior knowledge required

Time to complete the course

7-day free trial

No unnecessary risks

Skills you will acquire in the course

  • Image processing
  • Image features
  • Building a 3D scene
  • Image segmentation
  • Object recognition

What you will learn in the course

Courses for which the course is suitable

  • Computer Vision Engineer
  • Software developer in the field of computer vision
  • Computer vision researcher
  • Data analyst in the field of computer vision
  • Image processing expert
  • Develops object recognition algorithms
  • 3D Engineer
  • Developer of automatic image recognition systems
  • Project Manager in the Field of Computer Vision
  • Technology consultant in the field of computer vision

Internship – Series of 5 courses

This specialization presents the first comprehensive treatment of the fundamentals of computer vision. The course focuses on the mathematical and physical foundations of vision and is intended for learners, professionals, and researchers with no prior knowledge of computer vision. The program includes a series of 5 courses.

Any learner who completes this specialization will be able to build a successful career in computer vision, a growing field that is expected to become more important in the coming years.

Hands-on Learning Project

Learners will develop basic knowledge in computer vision by implementing models and tools such as:

  • Image processing
  • Image features
  • Building a 3D scene
  • Image segmentation
  • Object recognition

The specialization includes approximately 250 assessment questions. Mastery of the basics of computer vision is considered highly valuable in technology companies and diverse research organizations.

Details of the courses that make up the specialization

Camera and image

Course 1

20 hours

4.7 (130 ratings)

What will you learn?

  • Learn how a camera works and how an image is created using a lens.
  • Understand how the image sensor works and what its main characteristics are
  • Develop cameras that capture images in high dynamic range and at wide angles
  • Learn to create binary images and use them to build a simple object recognition system

Skills you will gain

  • Scale area
  • Solving any problems
  • Line and corner detection
  • Active borders
  • Image transformations

Course 2

24 hours

4.8 (42 ratings)

What will you learn?

  • Learn how to detect lines and corners in images.
  • Develop active boundaries (skin) to find complex object boundaries.
  • To get to know the logical essence of finding simple parametric shapes in images.
  • Learn about image transformations and how to estimate the homography between two images.

Skills you will gain

  • Image segmentation
  • Computer vision
  • Artificial neural networks
  • tracing
  • The match between the appearance

3D reconstruction – single point of view

Course 3

89 hours

4.9 (35 ratings)

What will you learn?

  • Learn about radiometric principles relating to light and how it interacts with scenes.
  • Understand models of reflection and the various physical mechanisms that determine the appearance of surfaces.
  • Develop a method for recovering the shape of a surface from its shading.
  • Familiarize yourself with the stereo photometric principle where a compressed map of the surface’s normals is achieved by changing the direction of illumination.

Skills you will gain

  • Stereo photometry
  • Built-in light methods
  • Sharpener depth and non-sharpener
  • Reflection models
  • Radiometry

3D reconstruction – multiple perspectives

Course 4

72 hours

4.7 (39 ratings)

What will you learn?

  • Develop a comprehensive model of a camera and learn how to type a camera by evaluating its parameters.
  • Develop a simple stereo system that uses two cameras of known configuration to estimate the three-dimensional structure of a scene.
  • Design an algorithm to recover both the structure of the scene and the camera movement from a video.
  • Develop optical flow algorithms for estimating the movement of points in a video sequence.

Skills you will gain

  • Camera model
  • Camera calibration
  • Epipolar geometry
  • Simple stereo
  • Structure from movement

Visual perception

Course 5

82 hours

4.6 (29 ratings)

What will you learn?

  • Learn about the principles of visual perception and how they affect the understanding of images.
  • Develop image analysis abilities and understanding of visual processes.

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