Dynamic Building Tracking from UAVs Based on Image Manifold Learning

DOI

10.2991/iccia.2012.240How to use a DOI?

Keywords

manifold learning, dynamic visual tracking, unmanned aerial vehicles.

Abstract

Fast and accurate visual tracking of ground buildings can provide unmanned aerial vehicles (UAVs) with rich perceptual information, which is very important for target recognition, navigation and system control. However, when an UAV moves fast, both background and buildings in visual scenes change relatively and rapidly. Consequently, there are no constant features for objects' appearance, which poses great challenges for visual tracking of buildings. In this paper, we first build an image manifold of buildings, which can encode the continuous variation of appearance. We then propose an efficient approach to learn this manifold and obtain more robust feature extraction results. By using a simple tracking framework, we successfully apply the extracted low-dimensional features to real-time building tracking. Experimental results demonstrate the effectiveness of the proposed method.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Peng Zhang
AU  - Yuanyuan Ren
PY  - 2014/05
DA  - 2014/05
TI  - Dynamic Building Tracking from UAVs Based on Image Manifold Learning
BT  - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)
PB  - Atlantis Press
SP  - 982
EP  - 985
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccia.2012.240
DO  - 10.2991/iccia.2012.240
ID  - Zhang2014/05
ER  -