Object Segmentation Using Background Modelling and Cascaded Change Detection

— 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 cumbersome 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 partitiondistance 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 ch...

• Type: Journal
• Year: 2007
• Where: JMM2
• Authors: Luís Filipe Teixeira, Jaime S. Cardoso, Luís Corte-Real
• Keywords: Captured Visual Scene, JMM2 2007, Structural Changes, first Step