Skip navigation
Skip navigation

Learning on lie groups for invariant detection and tracking

Tuzel, Oncel; Porikli, Fatih; Meer, Peter


This paper presents a novel learning based tracking model combined with object detection. The existing techniques proceed by linearizing the motion, which makes an implicit Euclidean space assumption. Most of the transformations used in computer vision have matrix Lie group structure. We learn the motion model on the Lie algebra and show that the formulation minimizes a first order approximation to the geodesic error. The learning model is extended to train a class specific tracking function,...[Show more]

CollectionsANU Research Publications
Date published: 2008
Type: Conference paper
Source: Proceedings of CVPR 2008
DOI: 10.1109/CVPR.2008.4587521


File Description SizeFormat Image
01_Tuzel_Learning_on_lie_groups_for_2008.pdf3.26 MBAdobe PDF    Request a copy

Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.

Updated:  23 August 2018/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator