Facial Detection and Recognition using OpenCV (BONUS: Create your own Snapchat Filter!) Video
- Be able to explain how computer vision works. Computer vision is the way of teaching intelligence to machines and teaching machines to view the world just as humans do. Examples are provided such as self-driving cars.
- Learn about OpenCV (Open Source Computer Vision Library). This library contains over 2,500 optimized computer vision and machine learning algorithms.
- Install OpenCV and start working with images.
- Read a video stream from the webcam frame by frame using OpenCV.
- Perform face detection using OpenCV and the Haar Cascade Classifier.
- Generate the face recognition training dataset. Extract images from the Webcam and detect faces and draw bounding boxes around each face.
- Apply the K-Nearest Neighbors supervised learning algorithm on the Iris flower dataset for face recognition.
- Perform face recognition.
- Create a face recognition algorithm and test it by identifying images in a video stream. Then use the algorithm to match a face with an identifier.
- Create a pig nose Snapchat filter using OpenCV.
- Install and work with other libraries including dlib.
Instructor: Advait Jayant
Length: 3 hours
Access period: For one year starting from purchase date