A HMM approach to the estimation of random trajectories on manifolds

Dynamic image analysis requires the estimation of time-varying model parameters (e.g., shape coe cients). This can be11 seen as states of a dynamic model which are restricted to a subset of Euclidean space. This paper describes an algorithm for the estimation of the state evolution on manifolds exploiting three sources of information: the manifold geometry, the13 motion model and the sensor model. Examples are provided to illustrate the performance of this method in situations where classic procedures cannot perform well. ? 2002 Published by Elsevier Science B.V.15

• Type: Journal
• Year: 2002
• Where: SIGPRO
• Authors: Jorge S. Marques, João Miranda Lemos, Arnaldo J. Abrantes
• Keywords: Dynamic Image Analysis, Model, SIGPRO 2002, Time-varying Model Parameters