IEICE TRANSACTIONS on Communications
Adaptive Multi-Scale Tracking Target Algorithm through Drone
Summary :
In order to solve the influence of scale change on target tracking using the drone, a multi-scale target tracking algorithm is proposed which based on the color feature tracking algorithm. The algorithm realized adaptive scale tracking by training position and scale correlation filters. It can first obtain the target center position of next frame by computing the maximum of the response, where the position correlation filter is learned by the least squares classifier and the dimensionality reduction for color features is analyzed by principal component analysis. The scale correlation filter is obtained by color characteristics at 33 rectangular areas which is set by the scale factor around the central location and is reduced dimensions by orthogonal triangle decomposition. Finally, the location and size of the target are updated by the maximum of the response. By testing 13 challenging video sequences taken by the drone, the results show that the algorithm has adaptability to the changes in the target scale and its robustness along with many other performance indicators are both better than the most state-of-the-art methods in illumination Variation, fast motion, motion blur and other complex situations.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E102-B No.10 pp.1998-2005
- Publication Date
- 2019/10/01
- Publicized
- 2019/04/26
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2018DRP0040
- Type of Manuscript
- Special Section PAPER (Special Section on Exploring Drone for Mobile Sensing, Coverage and Communications: Theory and Applications)
- Category
Authors
Qiusheng HE
Taiyuan University of Science and Technology
Xiuyan SHAO
University of Oulu
Wei CHEN
China University of Mining and Technology,Xi'an University of Science and Technology
Xiaoyun LI
Taiyuan University of Science and Technology
Xiao YANG
China University of Mining and Technology
Tongfeng SUN
China University of Mining and Technology
Keyword
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Qiusheng HE, Xiuyan SHAO, Wei CHEN, Xiaoyun LI, Xiao YANG, Tongfeng SUN, "Adaptive Multi-Scale Tracking Target Algorithm through Drone" in IEICE TRANSACTIONS on Communications,
vol. E102-B, no. 10, pp. 1998-2005, October 2019, doi: 10.1587/transcom.2018DRP0040.
Abstract: In order to solve the influence of scale change on target tracking using the drone, a multi-scale target tracking algorithm is proposed which based on the color feature tracking algorithm. The algorithm realized adaptive scale tracking by training position and scale correlation filters. It can first obtain the target center position of next frame by computing the maximum of the response, where the position correlation filter is learned by the least squares classifier and the dimensionality reduction for color features is analyzed by principal component analysis. The scale correlation filter is obtained by color characteristics at 33 rectangular areas which is set by the scale factor around the central location and is reduced dimensions by orthogonal triangle decomposition. Finally, the location and size of the target are updated by the maximum of the response. By testing 13 challenging video sequences taken by the drone, the results show that the algorithm has adaptability to the changes in the target scale and its robustness along with many other performance indicators are both better than the most state-of-the-art methods in illumination Variation, fast motion, motion blur and other complex situations.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2018DRP0040/_p
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@ARTICLE{e102-b_10_1998,
author={Qiusheng HE, Xiuyan SHAO, Wei CHEN, Xiaoyun LI, Xiao YANG, Tongfeng SUN, },
journal={IEICE TRANSACTIONS on Communications},
title={Adaptive Multi-Scale Tracking Target Algorithm through Drone},
year={2019},
volume={E102-B},
number={10},
pages={1998-2005},
abstract={In order to solve the influence of scale change on target tracking using the drone, a multi-scale target tracking algorithm is proposed which based on the color feature tracking algorithm. The algorithm realized adaptive scale tracking by training position and scale correlation filters. It can first obtain the target center position of next frame by computing the maximum of the response, where the position correlation filter is learned by the least squares classifier and the dimensionality reduction for color features is analyzed by principal component analysis. The scale correlation filter is obtained by color characteristics at 33 rectangular areas which is set by the scale factor around the central location and is reduced dimensions by orthogonal triangle decomposition. Finally, the location and size of the target are updated by the maximum of the response. By testing 13 challenging video sequences taken by the drone, the results show that the algorithm has adaptability to the changes in the target scale and its robustness along with many other performance indicators are both better than the most state-of-the-art methods in illumination Variation, fast motion, motion blur and other complex situations.},
keywords={},
doi={10.1587/transcom.2018DRP0040},
ISSN={1745-1345},
month={October},}
Copy
TY - JOUR
TI - Adaptive Multi-Scale Tracking Target Algorithm through Drone
T2 - IEICE TRANSACTIONS on Communications
SP - 1998
EP - 2005
AU - Qiusheng HE
AU - Xiuyan SHAO
AU - Wei CHEN
AU - Xiaoyun LI
AU - Xiao YANG
AU - Tongfeng SUN
PY - 2019
DO - 10.1587/transcom.2018DRP0040
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E102-B
IS - 10
JA - IEICE TRANSACTIONS on Communications
Y1 - October 2019
AB - In order to solve the influence of scale change on target tracking using the drone, a multi-scale target tracking algorithm is proposed which based on the color feature tracking algorithm. The algorithm realized adaptive scale tracking by training position and scale correlation filters. It can first obtain the target center position of next frame by computing the maximum of the response, where the position correlation filter is learned by the least squares classifier and the dimensionality reduction for color features is analyzed by principal component analysis. The scale correlation filter is obtained by color characteristics at 33 rectangular areas which is set by the scale factor around the central location and is reduced dimensions by orthogonal triangle decomposition. Finally, the location and size of the target are updated by the maximum of the response. By testing 13 challenging video sequences taken by the drone, the results show that the algorithm has adaptability to the changes in the target scale and its robustness along with many other performance indicators are both better than the most state-of-the-art methods in illumination Variation, fast motion, motion blur and other complex situations.
ER -
English
