Introduction to Computer Vision

Online Course

Udacity

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What is the course about?
Prerequisites & Facts
Cost, Certificate & Degree
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What is the course about?

Introduction to Computer Vision

The course Introduction to Computer Vision is an online class provided by Udacity. The skill level of the course is Intermediate. It may be possible to receive a verified certification or use the course to prepare for a degree.

This course provides an introduction to computer vision including fundamentals of image formation, camera imaging geometry, feature detection and matching, multiview geometry including stereo, motion estimation and tracking, and classification. We’ll develop basic methods for applications that include finding known models in images, depth recovery from stereo, camera calibration, image stabilization, automated alignment (e.g. panoramas), tracking, and action recognition. We focus less on the machine learning aspect of CV as that is really classification theory best learned in an ML course.

Course description

Introduction to Computer Vision
4 months

Offered at Georgia Tech as CS 6476
Build Deep Learning Models Today
The focus of the course is to develop the intuitions and mathematics of the methods in lecture, and then to learn about the difference between theory and practice in the problem sets. All algorithms work perfectly in the slides. But remember what Yogi Berra said: In theory there is no difference between theory and practice. In practice there is. (Einstein said something similar but who knows more about real life?) In this course you do not, for the most part, apply high-level library functions but use low to mid level algorithms to analyze images and extract structural information.

Introduction
Image Processing for Computer Vision
Camera Models and Views
Image Features
Lighting
Image Motion
Tracking
Classification and Recognition
Useful Methods
Human Visual System

Introduction
Linear image processing
Model fitting
Frequency domain analysis
Camera models
Stereo geometry
Camera calibration
Multiple views
Feature detection
Feature descriptors
Model fitting
Photometry
Lightness
Shape from shading
Overview
Optical flow
Introduction to tracking
Parametric models
Non-parametric models
Tracking considerations
Introduction to recognition
Classification: Generative models

See the Technology Requirements for using Udacity.

Images have become ubiquitous in computing. Sometimes we forget that images often capture the light reflected from a physical scene. This course gives you both insight into the fundamentals of image formation and analysis, as well as the ability to extract information much above the pixel level. These skills are useful for anyone interested in operating on images in a context-aware manner or where images from multiple scenarios need to be combined or organized in an appropriate way.

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Prerequisites & Facts

Introduction to Computer Vision

Course Topic

Deep Learning

University, College, Institution

Udacity

Course Skill Level

Intermediate

see course summary

Course Language

English

Place of class

Online, self-paced (see curriculum for more information)

Degree

Certificate

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Degree & Cost

Introduction to Computer Vision

To obtain a verified certificate from Udacity you have to finish this course or the latest version of it, if there is a new edition. The class may be free of charge, but there could be some cost to receive a verified certificate or to access the learning materials. The specifics of the course may have been changed, please consult the provider to get the latest quotes and news.

Udacity

Introduction to Computer Vision

provided by Udacity

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