OpenCV is a library of programming functions mainly aimed at real-time computer vision. Originally developed by Intel, it was later supported by Willow Garage then Itseez. The library is cross-platform and free for use under the open-source Apache 2 License.(Wikipedia)
It is one of the most popular tools for facial recognition, used in a wide variety of security, marketing, and photography applications, and it powers a lot of cutting-edge tech, including augmented reality and robotics. This course offers Python developers a detailed introduction to OpenCV 3, starting with installing and configuring your Mac, Windows, or Linux development environment along with Python 3. Learn about the data and image types unique to OpenCV, and find out how to manipulate pixels and images. Then comes the real power of OpenCV: object, facial, and feature detection. Learn how to leverage the image-processing power of OpenCV using methods like template matching and machine learning data to identify and recognise features.
Introduction to OpenCV
Installation & Personalisation
Basic operations
Pixel Data, Data Types, Structures
Pixel manipulation & filtering
Object Detection with OpenCV
Segmentation & Binary Images
Simple & Adaptive Thresholds
Contours , Area perimeters, Center & Curvature
Object, Canny Edges Detection
Assignments
Areas of Application
2D & 3D Toolkits
Egomotion Estimation
Facial & Gesture recognition
Human computer interaction
Mobile robotics
SFM
Motion Tracking
Augmented Reality
Object Detection
Segmentation & Recognition
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