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 mu m-12 mu m 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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