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Image Classification with Multivariate Gaussian Descriptors

  • Costantino Grana
  • Giuseppe Serra
  • Marco Manfredi
  • Rita Cucchiara
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8157)

Abstract

Techniques based on Bag Of Words approach represent images by quantizing local descriptors and summarizing their distribution in a histogram. Differently, in this paper we describe an image as multivariate Gaussian distribution, estimated over the extracted local descriptors. The estimated distribution is mapped to a high-dimensional descriptor, by concatenating the mean vector and the projection of the covariance matrix on the Euclidean space tangent to the Riemannian manifold. To deal with large scale datasets and high dimensional feature spaces the Stochastic Gradient Descent solver is adopted. The experimental results on Caltech-101 and ImageCLEF2011 show that the method obtains competitive performance with state-of-the art approaches.

Keywords

image retrieval image classification multi-class multi-label stochastic gradient descent 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Costantino Grana
    • 1
  • Giuseppe Serra
    • 1
  • Marco Manfredi
    • 1
  • Rita Cucchiara
    • 1
  1. 1.Università degli Studi di Modena e Reggio EmiliaModenaItaly

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