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Camouflaged Person Identification

  • Rajiv Singh
  • Swati Nigam
  • Amit Kumar Singh
  • Mohamed Elhoseny
Chapter
  • 27 Downloads

Abstract

This chapter proposes a new method of camouflaged person identification that combines discrete wavelet coefficients with support vector machine (SVM) classifier. Multiresolution property of wavelet transform provides invariant person identification against camouflaged scenes and do not get affected by similar foreground and background objects. Flexibility of wavelet and SVM makes the proposed method robust while providing better efficiency. For evaluation of the proposed method, we have experimented it over CAMO_UOW dataset. From objective evaluation it is clear that proposed approach outperforms existing camouflaged person identification approaches. The proposed methodology is simple and does not depend on a specific special resolution. It is suitable for detecting camouflaged persons in the images or videos where foreground and background are almost similar.

Keywords

Person detection Camouflaged data Ambiguous background F-measure 

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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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