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