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基于壓縮特征的魚眼視頻目標跟蹤算法研究

李雅倩 賈璐 李海濱 張文明 張巖松

李雅倩, 賈璐, 李海濱, 張文明, 張巖松. 基于壓縮特征的魚眼視頻目標跟蹤算法研究[J]. 電子與信息學報, 2018, 40(5): 1242-1249. doi: 10.11999/JEIT170745
引用本文: 李雅倩, 賈璐, 李海濱, 張文明, 張巖松. 基于壓縮特征的魚眼視頻目標跟蹤算法研究[J]. 電子與信息學報, 2018, 40(5): 1242-1249. doi: 10.11999/JEIT170745
LI Yaqian, JIA Lu, LI Haibin, ZHANG Wenming, ZHANG Yansong. Research on Target Tracking Algorithm from Fisheye Camera Based on Compressive Sensing[J]. Journal of Electronics & Information Technology, 2018, 40(5): 1242-1249. doi: 10.11999/JEIT170745
Citation: LI Yaqian, JIA Lu, LI Haibin, ZHANG Wenming, ZHANG Yansong. Research on Target Tracking Algorithm from Fisheye Camera Based on Compressive Sensing[J]. Journal of Electronics & Information Technology, 2018, 40(5): 1242-1249. doi: 10.11999/JEIT170745

基于壓縮特征的魚眼視頻目標跟蹤算法研究

doi: 10.11999/JEIT170745
基金項目: 

河北省自然科學基金(F2015203212)

Research on Target Tracking Algorithm from Fisheye Camera Based on Compressive Sensing

Funds: 

The Natural Science Foundation of Hebei Province (F2015203212)

  • 摘要: 該文針對畸變嚴重的魚眼圖像中的目標跟蹤,提出一種能適應尺度變化、姿態(tài)變化以及形狀畸變的魚眼視頻目標跟蹤的方法。該方法首先將灰度特征和相對梯度特征相結合得到目標的高維特征,然后對其平均降維得到目標的壓縮特征。并根據(jù)魚眼成像模型得到投影點的運動特性,確定目標的運動范圍。為了適應尺度變化,在塊匹配運動估計思想的基礎上,對目標跟蹤框的頂點分別進行由粗到精的定位,并在此過程中根據(jù)跟蹤框的尺度相應改變壓縮特征的尺度。實驗結果表明:該算法在目標畸變、尺度變化、姿態(tài)變化以及局部遮擋等情況下,判斷指標均優(yōu)于其他對比算法。
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計量
  • 文章訪問數(shù):  1442
  • HTML全文瀏覽量:  180
  • PDF下載量:  177
  • 被引次數(shù): 0
出版歷程
  • 收稿日期:  2017-07-21
  • 修回日期:  2018-01-24
  • 刊出日期:  2018-05-19

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