October 2013 Embedded Vision Summit Technical Presentation: "Embedded Lucas-Kanade Tracking: How it Works, How to Implement It, and How to Use It," Goksel Dedeoglu, Texas Instruments
Registration is free and takes less than one minute. Click here to register, and get full access to the Embedded Vision Academy's unique technical training content.
If you've already registered, click here to sign in.
See a sample of this page's content below:
Goksel Dedeoglu, Embedded Vision R&D Manager at Texas Instruments, presents the "Embedded Lucas-Kanade Tracking: How it Works, How to Implement It, and How to Use It" tutorial within the "Algorithms and Implementations" technical session at the October 2013 Embedded Vision Summit East.
This tutorial is intended for technical audiences interested in learning about the Lucas-Kanade (LK) tracker, also known as the Kanade-Lucas-Tomasi (KLT) tracker. Invented in the early 80s, this method has been widely used to estimate pixel motion between two consecutive frames. Dedeoglu presents how the LK tracker works and discuss its advantages, limitations, and how to make it more robust and useful. Using DSP-optimized functions from TI's Vision Library (VLIB), he also shows how to detect feature points in real-time and track them from one frame to the next using the LK algorithm.