Computer Vision with MATLAB for Object Detection and Tracking

From the series: Computer Vision with MATLAB

Bruce Tannenbaum, MathWorks

Computer vision uses images and video to detect, classify, and track objects or events in order to understand a real-world scene. In this webinar, we dive deeper into the topic of object detection and tracking. Through product demonstrations, you will see how to:

  • Recognize objects using SURF features
  • Detect faces and upright people with algorithms such as Viola-Jones
  • Track single objects with the Kanade-Lucas-Tomasi (KLT) point tracking algorithm
  • Perform Kalman Filtering to predict the location of a moving object
  • Implement a motion-based multiple object tracking system

This webinar assumes some experience with MATLAB and Image Processing Toolbox. We will focus on the Computer Vision System Toolbox.

About the Presenter: Bruce Tannenbaum works on image processing and computer vision applications in technical marketing at MathWorks. Earlier in his career, he developed computer vision and wavelet-based image compression algorithms at Sarnoff Corporation (SRI). He holds an MSEE degree from University of Michigan and a BSEE degree from Penn State.

View example code from this webinar here: http://www.mathworks.com/matlabcentral/fileexchange/40079

Product Focus

  • Computer Vision System Toolbox

Recorded: 29 Jan 2013

Series: Computer Vision with MATLAB

Computer Vision Made Easy
In this introductory webinar you will learn how to use computer vision algorithms to solve real world imaging problems. Computer vision uses images and video to detect, classify, and track objects or events in order to understand a real-world scene.

Computer Vision with MATLAB for Object Detection and Tracking
Computer vision uses images and video to detect, classify, and track objects or events in order to understand a real-world scene. In this webinar, we dive deeper into the topic of object detection and tracking.

Face Recognition with MATLAB
Recognize faces using machine learning and computer vision techniques.