The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper, we propose an unsupervised salient object segmentation approach based on kernel density estimation (KDE) and two-phase graph cut. A set of KDE models are first constructed based on the pre-segmentation result of the input image, and then for each pixel, a set of likelihoods to fit all KDE models are calculated accordingly. The color saliency and spatial saliency of each KDE model are...
This paper proposes a nonparametric saliency model based on kernel density estimation (KDE) mainly aiming at content-based applications such as salient object segmentation. A set of KDE models are constructed on the basis of regions segmented using the mean shift algorithm. For each pixel, a set of color likelihood measures to all KDE models are calculated, and then the color saliency and spatial...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.