INVESTIGADORES
SANCHEZ Jorge Adrian
artículos
Título:
Modeling the Spatial Layout of Images Beyond Spatial Pyramids
Autor/es:
JORGE SÁNCHEZ; FLORENT PERRONNIN; TEOFILO DE CAMPOS
Revista:
PATTERN RECOGNITION LETTERS
Editorial:
ELSEVIER SCIENCE BV
Referencias:
Lugar: Amsterdam; Año: 2012 p. 2216 - 2223
ISSN:
0167-8655
Resumen:
Several state-of-the-art image representations consist in
averaging local statistics computed from patch-level descriptors. It has
been shown by Boureau et al. that such average statistics suffer from
two sources of variance. The first one comes from the fact that a finite
set of local statistics are averaged. The second one is due to the
variation in the proportion of object-dependent information between
different images of the same class. For the problem of object
classification, these sources of variance affect negatively the accuracy
since they increase the overlap between class-conditional
probabilities.
Our goal is to include information about
the spatial layout of images in image signatures based on average
statistics. We show that the traditional approach to including the
spatial layout ? the spatial pyramid (SP) ? increases the first source
of variance while only weakly reducing the second one. We therefore
propose two complementary approaches to account for the spatial layout
which are compatible with our goal of variance reduction. The first one
models the spatial layout in an image-independent manner (as is the case
of the SP) while the second one adapts to the image content. A
significant benefit of these approaches with respect to the SP is that
they do not incur an increase of the image signature dimensionality. We
show on PASCAL VOC 2007, 2008 and 2009 the benefits of our approach.