Title :
Dynamic trees for sensor fusion
Author :
Kampa, Kittipat ; Slatton, K. Clint ; Cobb, J. Tory
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Florida, Gainesville, FL, USA
Abstract :
The dynamic tree (DT) graphical model is a popular analytical framework for image segmentation and object classification tasks. A DT is a useful model in this context because its hierarchical property encodes information in multiple scales and its flexible structure fits complex region boundaries better 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 combine common information across different sensor measurements of simulated objects of interest. The appropriate structure of the DT and its parameters for the data fusion application are presented and discussed along with fusion results from a simulated sonar survey mission.
Keywords :
image classification; image segmentation; sensor fusion; trees (mathematics); data fusion; dynamic tree graphical model; image segmentation; object classification; sensor fusion; sensor measurements; simulated sonar survey mission; tree-structured Bayesian networks; Bayesian methods; Classification tree analysis; Context modeling; Flexible structures; Fuses; Graphical models; Image analysis; Image segmentation; Sensor fusion; Tree graphs; belief propagation; dynamic tree; sonar; tree-structured Bayesian network;
Conference_Titel :
Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
978-1-4244-2793-2
Electronic_ISBN :
1062-922X
DOI :
10.1109/ICSMC.2009.5346574