Kernel-Based Motion-Blurred Target Tracking

  • Yi Wu
  • Jing Hu
  • Feng Li
  • Erkang Cheng
  • Jingyi Yu
  • Haibin Ling
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6939)


Motion blurs are pervasive in real captured video data, especially for hand-held cameras and smartphone cameras because of their low frame rate and material quality. This paper presents a novel Kernel-based motion-Blurred target Tracking (KBT) approach to accurately locate objects in motion blurred video sequence, without explicitly performing deblurring. To model the underlying motion blurs, we first augment the target model by synthesizing a set of blurred templates from the target with different blur directions and strengths. These templates are then represented by color histograms regularized by an isotropic kernel. To locate the optimal position for each template, we choose to use the mean shift method for iterative optimization. Finally, the optimal region with maximum similarity to its corresponding template is considered as the target. To demonstrate the effectiveness and efficiency of our method, we collect several video sequences with severe motion blurs and compare KBT with other traditional trackers. Experimental results show that our KBT method can robustly and reliably track strong motion blurred targets.


Target Model Color Histogram Visual Tracking Motion Blur Blur Kernel 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Yi Wu
    • 1
    • 2
    • 3
  • Jing Hu
    • 5
  • Feng Li
    • 4
  • Erkang Cheng
    • 3
  • Jingyi Yu
    • 4
  • Haibin Ling
    • 3
  1. 1.Jiangsu Engineering Center of Network MonitoringNanjing University of Information Science & TechnologyNanjingChina
  2. 2.School of Computer & SoftwareNanjing University of Information Science & TechnologyNanjingChina
  3. 3.Center for Information Science and Technology, Computer and Information Science DepartmentTemple UniversityPhiladelphiaUSA
  4. 4.Department of Computer and Information SciencesUniversity of DelawareNewarkUSA
  5. 5.Network CenterNanjing University of Information Science & TechnologyNanjingChina

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