English | MP4 | AVC 1920×1080 | AAC 48KHz 2ch | 0h 29m | 148 MB
Computer vision is an exciting and growing field. There are tons of interesting problems to solve! One of them is face detection: the ability of a computer to recognize that a photograph contains a human face, and tell you where it is located. In this course, you’ll learn about face detection with Python.
To detect any object in an image, it is necessary to understand how images are represented inside a computer, and how that object differs visually from any other object.
Once that is done, the process of scanning an image and looking for those visual cues needs to be automated and optimized. All these steps come together to form a fast and reliable computer vision algorithm.
In this course, you’ll learn:
- What face detection is
- How computers understand features in images
- How to quickly analyze many different features to reach a decision
- How to use a minimal Python solution for detecting human faces in images
Table of Contents
1 Intro
2 Computer Vision Technologies
3 How Do Computers See Images
4 Features
5 Viola Jones
6 Haar-Like Features
7 Integral Images
8 Adaboost
9 Classifier Cascades
10 Using the Viola Jones Framework
11 Conclusion
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