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 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
