Mercredi 25 Mars 2009, Salle R, 14h

Differential Colour Structure: from edges to image statistics to
visual categorisation

Jan-Mark Geusebroek and Koen van de Sande
ISLA, University of Amsterdam

Abstract:

Colour is an intriguing source of information in images. Many aspects
of physics and human vision are inextricably linked in local image
patches.  This talk aims to shed light on the aspects of physics and
the differential observation of colour images. A natural starting
point is to investigate the physical formation process of
images. Visual appearance depends on the illuminant position and
intensity, the incidental viewpoint of the camera, material properties
of the objects, and the composition of the scene resulting in
occlusions and clutter. We follow the physics of light, as it is
emitted from the source, reflected by the materials in the scene, and
recorded by the camera (or human eye alike). By modeling the image
observation by a linear diffusion process, we end up with a
scale-space theory of colour image formation. This theory includes and
explains many properties of vision, like receptive fields, colour edge
detection, colour scale-space blurring, colour constancy, and last but
not least colour SIFT descriptors. Further combining colour
scale-space theory with natural image statistics yields a solid basis
for compact local statistics of images, allowing to capture gist of
scene like information.

We will show how colour information can be exploited in visual
categorisation. So far, intensity-based descriptors have been widely
used. To increase
illumination invariance and discriminative power, colour descriptors
have been proposed only recently. As many descriptors exist, a
structured overview is required of colour invariant descriptors in the
context of image categorisation. Therefore, we have studied 1. the
invariance properties and 2. the distinctiveness of colour descriptors
in a structured way. The invariance properties of colour descriptors
are shown analytically using a taxonomy based on invariance properties
with respect to photometric transformations. The distinctiveness of
colour descriptors is assessed experimentally by means of the PASCAL
Visual Object Classification challenge and the TRECvid video retrieval
benchmark.