Proceedings chapter

Joint learning of local fingerprint and content modulation

Presented at Kos (Greece), 28 Aug.-2 Sept. 2017
Publication date2017

This paper proposes learning a linear map with local content modulation for robust content fingerprinting. The goal is to estimate a data adapted linear map that provides bounded modulation distortion and features with targeted properties. A novel problem formulation is presented that jointly addresses the fingerprint learning and the content modulation. A solution by iterative alternating algorithm is proposed. The algorithm alternates between liner map update step and linear modulation estimate step. Global optimal solutions for the respective iterative steps are proposed, resulting in convergent algorithm with locally optimal solution. A computer simulation using local image patches, extracted from publicly available data set is provided. The advantages under additive white Gaussian noise (AWGN), lossy JPEG compression and projective geometrical transform distortions are demonstrated.

  • Active content fingerprint
  • Modulation
  • Feature map learning
  • Robustness
Citation (ISO format)
KOSTADINOV, Dimche, VOLOSHYNOVSKYY, Svyatoslav, FERDOWSI, Sohrab. Joint learning of local fingerprint and content modulation. In: 25th European Signal Processing Conference (EUSIPCO 2017). Kos (Greece). [s.l.] : IEEE, 2017. p. 276–280. doi: 10.23919/EUSIPCO.2017.8081212
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Proceedings chapter (Published version)

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