Computer Vision uses images and video to detect, classify and follow objects or events, to interpret scenes from the real world. In this webinar we delve into the subject of object detection and tracking. Through examples, attendees will learn how to:
- Recognize objects by using SURF features
- Detect faces and people using algorithms like Viola-Jones
- Complete tracking of a single object using the Kanade-Lucas-Tomasi (KLT) algorithm
- Use the Kalman Filter to predict the location of a moving object
- Implement a tracking system based on the movement of multiple objects
Aimed at: Engineers and scientists working on image, video or machine vision processing applications
We will focus on the Computer Vision System Toolbox using several examples:
- Object detection by using features
- People detection
- face recognition
- Tracking moving objects
Covers the following products
- Computer Vision System Toolbox
- Image Processing Toolbox
