Title :
Registering multiple cartographic models with the hierarchical mixture of experts algorithm
Author :
Moss, Simon ; Hancock, Edwin R.
Author_Institution :
Dept. of Comput. Sci., York Univ., UK
Abstract :
This paper describes an application of the hierarchical mixture of experts algorithm (HME) to the registration of multiple cartographic models to noisy radar data. According to the HME algorithm each model is represented by a set of maximum likelihood registration parameters together with a set of matching probabilities. This architecture can be viewed as providing simultaneous registration and hypothesis verification. The maps in the cartographic data-base compete to account for radar data through the imposed probability normalisation. The resulting matching algorithm can be regarded as a generic tool for model retrieval from a database. Our evaluation on radar images illustrates some of the characteristics of the algorithm. Our main conclusions are that the method is both robust to added image noise and poor initialisation
Keywords :
cartography; computer vision; database; experts algorithm; hierarchical mixture; hierarchical mixture of experts algorithm; hypothesis verification; image noise; initialisation; matching probabilities; maximum likelihood registration parameters; model retrieval; multiple cartographic models registration; noisy radar data; Application software; Computer science; Image recognition; Information retrieval; Machine vision; Navigation; Noise robustness; Radar applications; Radar imaging; Testing;
Conference_Titel :
Computer Vision and Pattern Recognition, 1997. Proceedings., 1997 IEEE Computer Society Conference on
Conference_Location :
San Juan
Print_ISBN :
0-8186-7822-4
DOI :
10.1109/CVPR.1997.609436