Object Tracking

  • Rajiv Singh
  • Swati Nigam
  • Amit Kumar Singh
  • Mohamed Elhoseny


Object tracking is core probelm in computer vision for effective video surveillance. Wavelet based tracking techniques have emerged as a powerful tool. We have exploited newly emerged curvelet transform coefficients for video object tracking. Unlike existing methods, wavelet based tracking computes only wavelet coefficients and do not get affected by variations in object’s shape, size or color. However, we assumed that size of object does not change significantly in consecutive frames. A small change is permissible only. If we take long frame range, we see that object’s shape and size changes significantly. Experimentation demonstrates that curvelet transform is capable of tracking of single object as well as multiple objects. It is found superior when compared qualitatively and quantitatively with existing tracking methods.


Tracking Random motion Multiple objects Complex environment 


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Rajiv Singh
    • 1
  • Swati Nigam
    • 1
  • Amit Kumar Singh
    • 2
  • Mohamed Elhoseny
    • 3
  1. 1.Department of Computer ScienceBanasthali VidyapithBanasthaliIndia
  2. 2.Department of Computer Science & EngineeringNational Institute of TechnologyPatnaIndia
  3. 3.Faculty of Computers and InformationMansoura UniversityDakahliyaEgypt

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