Unified 3D models for multisensor image synthesis

A unified approach to modelling three dimensional objects for multisensory imagery and feature prediction is presented. The object representation is a modified volume-surface octree. This representation is well adapted for the simulations of the physical processes that affect the generation of the different imagery. Specifically, the model supports visual, thermal and laser radar imagery. It is shown that the volume-surface octree representation is well suited for thermal modeling of complex objects with non-homogeneities and heat generation. An octree intersection technique that incorporates non-homogeneities in the material composition of the object is described. A computationally efficient, implicit finite difference method is described for the simulation of energy flow within objects and between the object surface and the environment. The prediction of laser radar (ladar) images uses a statistical model to predict speckle noise, which allows the synthesis of realistic imagery. Examples of the multisensory imagery produced by this scheme are presented. The imagery and features values predicted by this unified modeling scheme may be used to train multisensor-based object recognition systems