Abstract
In this paper, we present a new recognition system
for the fast detection and classification of objects
in spatial 3D data. The system consists of two main
components: A biologically motivated attention
system and a fast classifier. Input is provided by a
3D laser scanner, mounted on an autonomous mobile
robot, that acquires illumination independent range
and reflectance data. These are rendered into images
and fed into the attention system that detects
regions of potential interest. The classifier is
applied only to a region of interest, yielding a
significantly faster classification that requires
only 30\% of the time of an exhaustive
search. Furthermore, both the attention and the
classification system benefit from the fusion of the
bi-modal data, considering more object properties
for the detection of regions of interest and a lower
false detection rate in classification.
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