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Kernel-Spectral-Clustering-Driven Motion Segmentation: Rotating-Objects First Trials

  • O. Oña-Rocha
  • J. A. Riascos-SalasEmail author
  • I. C. Marrufo-Rodríguez
  • M. A. Páez-Jaime
  • D. Mayorca-Torres
  • K. L. Ponce-Guevara
  • J. A. Salazar-Castro
  • D. H. Peluffo-Ordóñez
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1068)

Abstract

Time-varying data characterization and classification is a field of great interest in both scientific and technology communities. There exists a wide range of applications and challenging open issues such as: automatic motion segmentation, moving-object tracking, and movement forecasting, among others. In this paper, we study the use of the so-called kernel spectral clustering (KSC) approach to capture the dynamic behavior of frames - representing rotating objects - by means of kernel functions and feature relevance values. On the basis of previous research works, we formally derive a here-called tracking vector able to unveil sequential behavior patterns. As a remarkable outcome, we alternatively introduce an encoded version of the tracking vector by converting into decimal numbers the resulting clustering indicators. To evaluate our approach, we test the studied KSC-based tracking over a rotating object from the COIL 20 database. Preliminary results produce clear evidence about the relationship between the clustering indicators and the starting/ending time instance of a specific dynamic sequence.

Keywords

Kernels Motion tracking Spectral clustering 

Notes

Acknowledgments

Authors acknowledge the SDAS Research Group (www.sdas-group.com) for its valuable support.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • O. Oña-Rocha
    • 1
    • 2
  • J. A. Riascos-Salas
    • 3
    • 7
    Email author
  • I. C. Marrufo-Rodríguez
    • 4
  • M. A. Páez-Jaime
    • 4
  • D. Mayorca-Torres
    • 5
  • K. L. Ponce-Guevara
    • 6
  • J. A. Salazar-Castro
    • 7
  • D. H. Peluffo-Ordóñez
    • 1
    • 4
  1. 1.Universidad Técnica del NorteIbarraEcuador
  2. 2.Universidad de las Fuerzas Armadas - ESPESangolquíEcuador
  3. 3.SDAS Research GroupIbarraEcuador
  4. 4.Yachay Tech UniversityUrcuquíEcuador
  5. 5.Universidad MarianaPastoColombia
  6. 6.Universidade Federal de PernambucoRecifeBrazil
  7. 7.Corporación Universitaria Autónoma de NariñoPastoColombia

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