TY - GEN
T1 - Moving target detection via hierarchical spatiotemporal saliency analysis
AU - Du, Bin
AU - Ma, Long
AU - Zhuang, Yin
AU - Chen, He
AU - Soomro, Nouman Q.
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/1
Y1 - 2017/12/1
N2 - Automatic detection of moving targets is one of important research area in the remote sensing field. In this paper, we propose a method that accurately detects moving targets in aerial videos using hierarchical spatiotemporal saliency analysis. First, coarse motion regions are extracted by utilizing global temporal saliency analysis. Based on these local candidate regions, spatial saliency methods are used to obtain accurate description of targets. After fusing spatial and temporal saliency values, we can get refined results of the detection. Considering about the inter-frame consistency of motion, trajectory level analysis is added in the proposed method to eliminate false alarms. Experiments conducted on the VIVID dataset validate the effectiveness and efficiency of the proposed method.
AB - Automatic detection of moving targets is one of important research area in the remote sensing field. In this paper, we propose a method that accurately detects moving targets in aerial videos using hierarchical spatiotemporal saliency analysis. First, coarse motion regions are extracted by utilizing global temporal saliency analysis. Based on these local candidate regions, spatial saliency methods are used to obtain accurate description of targets. After fusing spatial and temporal saliency values, we can get refined results of the detection. Considering about the inter-frame consistency of motion, trajectory level analysis is added in the proposed method to eliminate false alarms. Experiments conducted on the VIVID dataset validate the effectiveness and efficiency of the proposed method.
KW - hierarchical analysis
KW - moving target detection
KW - spatiotemporal saliency
UR - http://www.scopus.com/inward/record.url?scp=85041855084&partnerID=8YFLogxK
U2 - 10.1109/IGARSS.2017.8127334
DO - 10.1109/IGARSS.2017.8127334
M3 - Conference contribution
AN - SCOPUS:85041855084
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 1840
EP - 1843
BT - 2017 IEEE International Geoscience and Remote Sensing Symposium
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017
Y2 - 23 July 2017 through 28 July 2017
ER -
