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We present an integrated pixel segmentation and region tracking algorithm, designed for indoor environments. Visual monitoring systems often use frame differencing techniques to independently classify each image pixel as either foreground or background. Typically, this level of processing does not take account of the global image structure, resulting in frequent misclassification. We use an adaptive Gaussian mixture model in colour and space to represent background and foreground regions of the scene. This model is used to probabilistically classify observed pixel values, incorporating the global scene structure into pixel-level segmentation. We evaluate our system over 4 sequences and show that it successfully segments foreground pixels and tracks major foreground regions as they move through the scene.

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Dickinson, Patrick -  Hunter, Andrew - 

Id.: 3980855

Versión: 1.0

Estado: Final

Tipo:  application/pdf - 

Palabras claveG740 Computer Vision - 

Tipo de recurso: Conference or Workshop Item  -  PeerReviewed  - 

Tipo de Interactividad: Expositivo

Nivel de Interactividad: muy bajo

Audiencia: Estudiante  -  Profesor  -  Autor  - 

Estructura: Atomic

Coste: no

Copyright: sí

Formatos:  application/pdf - 

Requerimientos técnicos:  Browser: Any - 

Relación: [References] http://dx.doi.org/10.1109/AVSS.2005.1577244
[References] http://eprints.lincoln.ac.uk/83/

Fecha de contribución: 19-jul-2011


* Dickinson, Patrick and Hunter, Andrew (2005) Scene modelling using an adaptive mixture of Gaussians in colour and space. In: IEEE Conference on Advanced Video and Signal based Surveillance, 15-15 Sept 2005, Como, Italy.

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