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.
Different datasets are often regarded as different domains where different data distributions exist in many pattern recognition systems. A typical problem is the different illumination conditions that need to be adapted in human skin detection. In this paper we present a method called rotation invariant ellipsoid projection (RIEP) to handle the domain transfer problem in the feature space. It uses...
Image edges, especially in the extracted silhouette, offered satisfied positional information for markerless vision-based motion capture. However, traditional bottom-up edge detection methods (such as canny operator) are powerless for edge detection with small luminance difference, especially when a self-occlusion happened. In this paper, we proposed a top-down edge detection method which can be viewed...
Video segmentation is a significant pre-process step in many video analysis systems. In consideration of many current video segmentation methods are time and memory consuming, we present an efficient method in this paper based on the Gaussian mixture model (GMM) with a backward updating model. The Gaussian mixture components produced by the current frame will be used to segment the next frame, and...
We propose a method for extracting a desired object in multi-view images without camera calibration. We match the corner points obtained automatically by the Scale-invariant feature transform (SIFT) in multiview images, and then connect multi-view images into a weighted undirected graph. Thus, multi-view object segmentation converts to a graph partitioning problem solved by Biased Normalized Cuts...
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.