As a guest user you are not logged in or recognized by your IP address. You have
access to the Front Matter, Abstracts, Author Index, Subject Index and the full
text of Open Access publications.
A precise background detection is required for video surveillance applications in order to detect foreground objects. However, in the presence of cluttered scenes, standard techniques for background segmentation can fail. In this work we present a new technique for foreground detection that is able to detect the correct background in complex scenes. It works grouping neighbour pixels that fulfill some kind of spatial and temporal criteria. Spatial criterion is based on the appearance similarity of neighbour pixels while temporal criterion looks for the best temporal correlation in the whole video sequence. Initially, a set of seed points of the image are selected and both criteria are applied in an alternate way until all the pixels of the image have been visited and their background value has been calculated.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.