Using optical flow as evidence for probabilistic tracking

Authors:
M. J. Lucena;J. M. Fuertes;N. Perez de la Blanca;A. Garrido
Affiliations:
Departamento de Informatica, Escuela Politecnica Superior, Universidad de Jaen, Jaen, Spain;Departamento de Informatica, Escuela Politecnica Superior, Universidad de Jaen, Jaen, Spain;Departamento de Ciencias de la Computacion e Inteligencia Artifficial, ETSII, Universidad de Granada, Granada, Spain;Departamento de Ciencias de la Computacion e Inteligencia Artifficial, ETSII, Universidad de Granada, Granada, Spain
Venue:
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
Year:
2003

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Abstract

In this paper, we presen t an observation model based on the Lucas and Kanade algorithm for computing optical flow, to trac k objects using particle filter algorithms. Although optical flow information enables us to know the displacement of objects present in a scene, it cannot be used directly to displace an object model since flow calculation techniques lack the necessary precision. In view of the fact that probabilistic tracking algorithms enable imprecise or incomplete information to be handled naturally, this model has been used as a natural means of incorporating flow information into the trac king.