Automatic tracking of flying vehicles using geodesic snakes and Kalman filtering

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Title: Automatic tracking of flying vehicles using geodesic snakes and Kalman filtering
Author: Betser, Amir ; Vela, Patricio A. ; Tannenbaum, Allen R.
Abstract: This paper describes a tracking algorithm relying on active contours for target extraction and an extended Kalman filter for relative pose estimation. This work represents the first step towards treating the general problem for the control of several unmanned autonomous vehicles flying in formation using only local visual information. In particular, we only allow on-board passive sensing. The problem is an excellent paradigm for studying the use of visual information in a feedback loop, the central theme of controlled active vision.
Description: ©2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
Type: Proceedings
ISSN: 0191-2216
ISBN: 0-7803-8682-5
Citation: A. Betser, A. Tannenbaum, and P. Vela, "Automatic tracking of flying vehicles using geodesic snakes and Kalman filtering," 43rd IEEE Conference on Decision and Control, 2004, Vol. 2, 1649-1654.
Date: 2004-12
Contributor: Georgia Institute of Technology. School of Electrical and Computer Engineering
Publisher: Georgia Institute of Technology
Institute of Electrical and Electronics Engineers
Subject: Kalman filters
Active vision
Feature extraction
Nonlinear filters
Remotely operated vehicles
Target tracking

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