TY - GEN
T1 - Object detection in remote sensing images based on one-class classification
AU - Wang, Tian
AU - Chen, Yang
AU - Qiao, Meina
AU - Zhu, Aichun
AU - Wang, Ziyu
AU - Snoussi, Hichem
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/29
Y1 - 2017/12/29
N2 - For remote sensing image understanding, target detection is one of the most important tasks. In this paper, we propose one object detection method based on region proposal detection via active contour model and detection based on one-class classification method. The large scale remote sensing image is split into several connected components. And then, the proposed algorithm detects the object from the background. The proposed algorithm has been tested on several scenes of real unmanned aerial vehicle image datasets, and achieves promising results.
AB - For remote sensing image understanding, target detection is one of the most important tasks. In this paper, we propose one object detection method based on region proposal detection via active contour model and detection based on one-class classification method. The large scale remote sensing image is split into several connected components. And then, the proposed algorithm detects the object from the background. The proposed algorithm has been tested on several scenes of real unmanned aerial vehicle image datasets, and achieves promising results.
KW - Active contour model
KW - Object detection
KW - One-class SVM
KW - Remote sensing image
UR - https://www.scopus.com/pages/publications/85050357128
U2 - 10.1109/CAC.2017.8243963
DO - 10.1109/CAC.2017.8243963
M3 - 会议稿件
AN - SCOPUS:85050357128
T3 - Proceedings - 2017 Chinese Automation Congress, CAC 2017
SP - 6583
EP - 6587
BT - Proceedings - 2017 Chinese Automation Congress, CAC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 Chinese Automation Congress, CAC 2017
Y2 - 20 October 2017 through 22 October 2017
ER -