Moving object detection in aerial video based on spatiotemporal saliency

被引:0
|
作者
Shen Hao [1 ]
Li Shuxiao [1 ]
Zhu Chengfei [1 ]
Chang Hongxing [1 ]
Zhang Jinglan [2 ]
机构
[1] Institute of Automaton,Chinese Academy of Sciences
[2] Queensland University of Technology,Brisbane,Australia
基金
中国国家自然科学基金;
关键词
Aerial video; Computer vision; Object detection; Saliency; Unmanned aerial vehicles;
D O I
暂无
中图分类号
V245.6 [照相设备];
学科分类号
082504 ;
摘要
In this paper,the problem of moving object detection in aerial video is addressed.While motion cues have been extensively exploited in the literature,how to use spatial information is still an open problem.To deal with this issue,we propose a novel hierarchical moving target detection method based on spatiotemporal saliency.Temporal saliency is used to get a coarse segmentation,and spatial saliency is extracted to obtain the object’s appearance details in candidate motion regions.Finally,by combining temporal and spatial saliency information,we can get refned detection results.Additionally,in order to give a full description of the object distribution,spatial saliency is detected in both pixel and region levels based on local contrast.Experiments conducted on the VIVID dataset show that the proposed method is effcient and accurate.
引用
收藏
页码:1211 / 1217
页数:7
相关论文
共 50 条
  • [1] Moving object detection in aerial video based on spatiotemporal saliency
    Shen Hao
    Li Shuxiao
    Zhu Chengfei
    Chang Hongxing
    Zhang Jinglan
    [J]. Chinese Journal of Aeronautics., 2013, 26 (05) - 1217
  • [2] Moving object detection in aerial video based on spatiotemporal saliency
    Shen Hao
    Li Shuxiao
    Zhu Chengfei
    Chang Hongxing
    Zhang Jinglan
    [J]. CHINESE JOURNAL OF AERONAUTICS, 2013, 26 (05) : 1211 - 1217
  • [3] Video Object Extraction Based on Spatiotemporal Consistency Saliency Detection
    Guo, Yingchun
    Li, Zhuo
    Liu, Yi
    Yan, Gang
    Yu, Ming
    [J]. IEEE ACCESS, 2018, 6 : 35171 - 35181
  • [4] Moving object properties-based video saliency detection
    Shang, Jinxia
    Liu, Yun
    Zhou, Huan
    Wang, Minghui
    [J]. JOURNAL OF ELECTRONIC IMAGING, 2021, 30 (02)
  • [5] Moving Object Detection in Aerial Video
    Wang, Yunfei
    Zhang, Zhaoxiang
    Wang, Yunhong
    [J]. 2012 11TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS (ICMLA 2012), VOL 2, 2012, : 446 - 450
  • [6] Highlight Moving Object Detection Based on Spatiotemporal Saliency in Dynamic Background
    Zhao, Yanxi
    Shang, Zhenhong
    Liu, Hui
    [J]. PROCEEDINGS OF 2015 THIRD IEEE WORLD CONFERENCE ON COMPLEX SYSTEMS (WCCS), 2015,
  • [7] Graph Cuts Based Moving Object Detection for Aerial Video
    Tong, Xiaomin
    Zhang, Yanning
    Yang, Tao
    Ma, Wenguang
    [J]. INTELLIGENCE SCIENCE AND BIG DATA ENGINEERING: IMAGE AND VIDEO DATA ENGINEERING, ISCIDE 2015, PT I, 2015, 9242 : 231 - 239
  • [8] Moving Object Segmentation in Video using Spatiotemporal Saliency and Laplacian Coordinates
    Ramadan, Hiba
    Tairi, Hamid
    [J]. 2016 IEEE/ACS 13TH INTERNATIONAL CONFERENCE OF COMPUTER SYSTEMS AND APPLICATIONS (AICCSA), 2016,
  • [9] Moving Object Detection System in Aerial Video Surveillance
    Walha, Ahlem
    Wali, Ali
    Alimi, Adel M.
    [J]. ADVANCED CONCEPTS FOR INTELLIGENT VISION SYSTEMS, ACIVS 2013, 2013, 8192 : 310 - 320
  • [10] Spatiotemporal saliency model for small moving object detection in infrared videos
    Wang, Xin
    Ning, Chen
    Xu, Lizhong
    [J]. INFRARED PHYSICS & TECHNOLOGY, 2015, 69 : 111 - 117