Object segmentation using background modelling and cascaded change detection

• Tipo: Artigo em Revista Científica Internacional
• Data: 2007

Autores

Teixeira, LF (Autor) Outra; Cardoso, JS (Autor) FEUP; Corte Real, L (Autor) FEUP

Revista

Título: Journal of Multimedia

Vol. 2 Nº 5

Páginas: 55-65

ISSN: 1796-2048

Editora: Academy Publisher

Indexação

ISI Web of Knowledge

Scopus - 16 Citações

Classificação Científica

CORDIS: Ciências Tecnológicas > Tecnologia > Tecnologia de computadores > Processamento de imagem

Outras Informações

ID Authenticus: P-007-NWA

DOI: 10.4304/jmm.2.5.55-65

Abstract (EN): The automatic extraction and analysis of visual information is becoming generalised. The first step in this processing chain is usually separating or segmenting the captured visual scene in individual objects. Obtaining a perceptually correct segmentation is however a cumber some task. Moreover, typical applications relying on object segmentation, such as visual surveillance, introduce two additional requirements: (1) it should represent only a small fraction of the total amount of processing time and (2) realtime overall processing. We propose a technique that tackles these problems using a cascade of change detection tests, including noise-induced, illumination variation and structural changes. An objective comparison of common pixelwise modelling methods is first done. A cost-based partition- distance between segmentation masks is introduced and used to evaluate the methods. Both the mixture of Gaussians and the kernel density estimation are used as a base to detect structural changes in the proposed algorithm. Experimental results show that the cascade technique consistently outperforms the base methods, without additional post-processing and without additional processing overheads. © 2007 ACADEMY PUBLISHER.

Idioma: Inglês

Tipo (Avaliação Docente): Científica