A framework for 3D polysensometric comparative visualization

Abstract

Typically any single sensor instrument suffers from physical/observation constraints. This paper discusses a generalized framework, called polysensometric visual information fusion framework (PVIF) that enables information from multiple sensors to be fused and compared to gain broader understanding of a target of observation. An automate software shell supporting comparative cognition has been developed to form 3D models based on the datasets from different sensors. This fusion framework not only provides an informatic engineering tool to overcome the constraints of individual sensor's observation scope but also provides a means where theoretical understanding surrounding a complex target can be mutually validated and incrementally enhanced by comparative cognition about the object of interest. © Springer-Verlag 2004.