Systems, Man, and Cybernetics

 

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• [P946] Dynamic Trees for Sensor Fusion
  Author(s): Kittipat Kampa, J. Tory Cobb, K. Clint Slatton
  
  

  Abstract
  The dynamic tree (DT) graphical model is a popular analytical tool for image segmentation and object classification tasks. A DT is a useful model in this context because its hierarchical property enables the user to examine information in multiple scales and its flexible configuration allows for flexibility in fitting complex region boundaries than rigid quadtree structures such as tree-structured Bayesian networks. This paper proposes a novel framework for data fusion by using a DT model to fuse measurements from multiple sensing platforms into a non-redundant representation. The structural flexibility of the DT will be used to fuse common information across different sensor measurements. The appropriate configuration of the DT and its parameters for the data fusion application are discussed. An example application is presented using simulated sonar images collected from a simulated survey mission and the fusion results using the presented DT optimization algorithm are discussed.

  
   

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