The recognition of dynamic textures is fundamental in processing image sequences as they are very common
in natural scenes. The computation of the optic flow is the most popular method to detect, segment and analyse
dynamic textures. For weak dynamic textures, this method is specially adequate. However, for strong dynamic
textures, it implies heavy computational load and therefore an important energy consumption. In this paper,
we propose a novel approach intented to be implemented by very low-power integrated vision devices. It
is based on a simple and flexible computation at the focal plane implemented by power-efficient hardware.
The first stages of the processing are dedicated to remove redundant spatial information in order to obtain
a simplified representation of the original scene. This simplified representation can be used by subsequent
digital processing stages to finally decide about the presence and evolution of a certain dynamic texture in the
scene. As an application of the proposed approach, we present the preliminary results of smoke detection for
the development of a forest fire detection system based on a wireless vision sensor network.Junta de Andalucía (CICE) 2006-TIC-235
