Details

Autor(en) / Beteiligte

• Jarrad, G.A.
• McMichael, D.W.

Titel

Shared mixture distributions and shared mixture classifiers

Ist Teil von

• 1999 Information, Decision and Control. Data and Information Fusion Symposium, Signal Processing and Communications Symposium and Decision and Control Symposium. Proceedings (Cat. No.99EX251), 1999, p.335-340

Ort / Verlag

IEEE

Erscheinungsjahr

1999

Quelle

IEEE Electronic Library (IEL)

Beschreibungen/Notizen

• The shared mixture classifier extends the conditional mixture classifier by allowing all the mixture components to contribute to the feature density model. We consider mixtures of elliptically symmetrical densities, and provide gradient ascent and expectation maximisation algorithms for maximum likelihood estimation. Three criteria are examined: the joint, non-discriminative and discriminative likelihoods. The relationships between these criteria are discussed, and we compare the performance of shared and conditional mixture classifiers. Results are presented for an application of a shared mixture classifier to the problem of detecting buried land mines using infrared and visual imagery. They show consistently better performance from the shared model.