Abstract
A unified approach for modeling objects which are imaged by
thermal (infrared) and visual cameras is presented. The model supports
the generation of both infrared (8 μm-12 μm wavelength) images and
monochrome visual images under different viewing and ambient-scene
conditions. A modified octree data structure is used for object
modeling. The octree serves two different purposes: surface information
encoded in boundary nodes and efficient tree-traversal algorithms
facilitate the generation of monochrome visual images; and the compact
volumetric representation facilitates simulation of heat flow in the
object which gives rise to surface temperature variation, which in turn
is used to synthesize the thermal image. The detailed object model
allows for more accurate prediction of thermal and visual images of
objects. It also predicts the values of discriminatory features used in
classification. The model developed is designed to be used in a
model-based vision system which uses a hypothesize-and-verify strategy
to interpret thermal and visual images of scenes. Several blocks-world
examples are presented to show typical images generated by the approach
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