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Camouflaged Person Identification

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Intelligent Wavelet Based Techniques for Advanced Multimedia Applications

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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.

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Authors and Affiliations

  1. Department of Computer Science, Banasthali Vidyapith, Banasthali, Rajasthan, India

    Rajiv Singh & Swati Nigam

  2. Department of Computer Science & Engineering, National Institute of Technology, Patna, Bihar, India

    Amit Kumar Singh

  3. Faculty of Computers and Information, Mansoura University, Dakahliya, Egypt

    Mohamed Elhoseny

Authors
  1. Rajiv Singh
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  2. Swati Nigam
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  3. Amit Kumar Singh
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  4. Mohamed Elhoseny
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Singh, R., Nigam, S., Singh, A.K., Elhoseny, M. (2020). Camouflaged Person Identification. In: Intelligent Wavelet Based Techniques for Advanced Multimedia Applications. Springer, Cham. https://doi.org/10.1007/978-3-030-31873-4_7

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  • DOI: https://doi.org/10.1007/978-3-030-31873-4_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-31872-7

  • Online ISBN: 978-3-030-31873-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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