A data fusion system for object recognition based on transferable belief models and kalman filters
Gavin Powell, Andrew D. Marshall, R. Milliken, Keith C. Markham · ORCA Online Research @Cardiff (Cardiff University) · 2004
We examine the use of fusing data from multiple data sources for use within object recognition systems. We then continue, to illustrate the system that we have created for our own object recognition needs. The data fusion model that we use is embedded within an object recognition system that analyses simulated FLIR and LADAR data to recognise and track aircraft. The data fusion is based upon the Transferable Belief Model (TBM) and Kalman filters. The system is novel due to the simulation of the sensors and the use of multiple Kalman filters and TBM’s.