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Two-Step Tracking by Parts Using Multiple Kernels

  • Autores: Brais Martínez, Luis Ferraz, Xavier Binefa i Valls Árbol académico
  • Localización: Artificial intelligence research and development / coord. por Beatriz López, Joaquim Meléndez Frigola Árbol académico, Petia Radeva Ivanova Árbol académico, Jordi Vitrià Marca Árbol académico, 2005, ISBN 978-1-58603-663-8, págs. 157-166
  • Idioma: inglés
  • Texto completo no disponible (Saber más ...)
  • Resumen
    • This paper addresses the problem of tracking IR image sequences by using kernel weighted histograms. The work is performed over the basis of the multiple kernel tracking algorithm presented in [3]. We present a new, novel, two-step tracking method which allows a tracking of independent parts of the same object by giving a higher flexibility to the multiple kernel model. This is performed by a progressive approximation of the movement by first estimating the global displacement with a multi-kernel estimator in order to have enough robustness and then, in the second step, the residual displacements of each part. The outcome is a method yet robust to partial occlusions, articulated motions or projectivities over the image with an application to partial occlusion detection and model update.

  • Referencias bibliográficas
    • [1] V. Ramesh V. Comaniciu and P. Meer: "Kernel-based object tracking," in Transactions on Pattern Analysis and Machine Intelligence,...
    • [2] Robert Collins, "Mean-shift blob tracking through scale space," in Computer Vision and Pattern Recognition (CVPR'03). June...
    • [3] Gregory D. Hager, Maneesh Dewan, and Charles V. Stewart, "Multiple kernel tracking with ssd.," in Computer Vision and Pattern...
    • [4] Alex Holub and Pietro Perona, "A discriminative framework for modeling object class," Computer Vision and Pattern Recognition...
    • [5] D. Nair and J.K. Aggarwal, "Bayesian recognition of targets by parts in second generation forward looking infrared images," Image...
    • [6] R. Fergus, P. Perona, and A. Zisserman, "Object class recognition by unsupervised scale-invariant learning," in Proceedings of...
    • [7] Iain Matthews and Takahiro Ishikawa and Simon Baker, "The Template Update Problem," in Proceedings of the British Machine Vision...
    • [8] Michael Isard and Andrew Blake, "Condensation - conditional density propagation for visual tracking", in International Journal...
    • [9] Grant Schindler and Frank Dellaert, "A Rao-Blackwellized Parts-Constellation Tracker", in ICCV Workshop on Dynamical Vision; International...

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