尚光网 本站首页 本所首页 联系我们
SCIDonoho DL, 2006, IEEE T INFORM THEORY, V52, P1289, DOI 10.1109/TIT.2006.871582; Gatti A, 2004, PHYS REV LETT, V93, DOI 10.1103/PhysRevLett.93.093602; Han G, 2016, SENSORS-BASEL, V16, DOI 10.3390/s16040456; He ZY, 2017, IEEE T CYBERNETICS, V47, P354, DOI 10.1109/TCYB.2016.2514714; Kajiki J, 2015, ASTROPHYSICS, V327, P90; Leihong Z, 2016, LASER PHYS, V26; Leihong Z, 2016, LASER PHYS, V26; Magana-Loaiza OS, 2013, APPL PHYS LETT, V102, DOI 10.1063/1.4809836; Morais AP, 2011, ELECTR POW SYST RES, V81, P1144, DOI 10.1016/j.epsr.2011.01.003; Prabhakar N., 2012, RES J APPL SCI ENG T, P5497; Pun CM, 2017, IEEE T INF FOREN SEC, V12, P377, DOI 10.1109/TIFS.2016.2615272; Shen YR, 2016, IEEE T MOBILE COMPUT, V15, P406, DOI 10.1109/TMC.2015.2418775; Shi H, 2016, J ALGORITHMS COMPUT, V10, P184; Sun T, 2016, APPL OPTICS, V55, P10335, DOI 10.1364/AO.55.010335; Yang Zhe, 2016, ARXIV160908741; Yasukawa S, 2016, NEURAL NETWORKS, V81, P29, DOI 10.1016/j.neunet.2016.05.002; Yu WK, 2015, APPL OPTICS, V54, P4249, DOI 10.1364/AO.54.004249; Zhang LH, 2016, J OPT SOC KOREA, V20, P515, DOI 10.3807/JOSK.2016.20.4.515; Zhu JZ, 2014, IET COMPUT VIS, V8, P740, DOI 10.1049/iet-cvi.2013.0255196097603183155Ukr. J. Phys. Opt.1432017object tracking; compressive sensing; ghost imaging; background subtractionREORTSOM217347Efficient object tracking represents a technology important for many vision applications. It is known that ghost imaging (GI) has a great potential if compared with a standard imaging and solves many problems in case if the common object tracking cannot be carried out. Here we show how the techniques of compressive GI and background subtraction can achieve object tracking. First, object information is captured with the GI. A characteristic measured for an object is obtained by subtracting background in the compressed domain. This characteristic uses compressive sensing to reconstruct the object image. Then the object image is projection-positioned to obtain the corresponding centroid coordinates. At last, the object trajectory is recovered with a polynomial fit, thus providing successful object tracking. Our simulation experiments suggest that the technique can track objects accurately under condition of low sampling ratios. Moreover, it decreases drastically the number of measurements needed for reconstruction and improves the tracking efficiency.Studies on the key methods for compressive ghost-image tracking based on background subtraction期刊论文EnglishZhang Leihong; Kang Yi; Li Bei; Zhan Wenjie; Zhang Dawei; Ma Xiuhua WOS:000406788600004
外文题目: Studies on the key methods for compressive ghost-image tracking based on background subtraction
作者: Zhang Leihong; Kang Yi; Li Bei; Zhan Wenjie; Zhang Dawei; Ma Xiuhua
刊名: Ukr. J. Phys. Opt.
年: 2017 卷: 18 期: 3 页: 143--155
英文关键词:
object tracking; compressive sensing; ghost imaging; background subtraction
英文摘要:
文献类型: 期刊论文
正文语种: English
收录类别: SCI  
全文传递服务
clickdetails
页面点击量: 4
文章下载量: 1
visitlog
友情链接:
  中国光学期刊网
  光电汇
  上海大恒公司
  南京先进激光技术院
  光学产品库
  上海研发公共服务平台
版权所有 © 2009 中国科学院上海光学精密机械研究所 沪ICP备05015387号
主办:中国科学院上海光学精密机械研究所 上海市嘉定区清河路390号(201800)