Lucas-Kanade Tracker (KLT) - Global Motion Estimation - Lecture 10

Explore the Lucas-Kanade Tracker (KLT) in this comprehensive lecture from the University of Central Florida's Computer Vision Video Lectures series. Delve into global motion estimation techniques, including tracking single points, bounding boxes, and object contours. Learn about multiple fixed and overlapping cameras, as well as tracking in moving cameras. Examine the KLT algorithm, its implementation, and results. Study 2-D transformations, displacement models, and their parameterizations. Understand the concepts of derivative, gradient, and displacement model Jacobians. Discover the process of finding alignment and the Hessian for translation motion. Gain valuable insights from Dr. Mubarak Shah's expertise in this hour-long video lecture, complemented by a detailed presentation for enhanced learning.

Global Motion Estimation
Tracking A Single Point
Tracking Bounding Boxes
Tracking Object Contours
Multiple Fixed & Overlapping Cameras
Tracking In Moving Camera
ECCV-2012
PETS2009-S2L1 Results
KLT(Kanade-Lucas-Tomasi) Tracker
Simple KLT Algorithm
KLT Results
Basic Set of 2-D Transformation
Summary of Displacement Models (2-D Transformations)
Displacement Models Parameterizations
Derivative & Gradient
Displacement Model Jacobians
Finding Alignment
Hessian for Translation Motion
Algorithm (KLT)