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.
This paper considers the problem of detecting actions from cluttered videos. Compared with the classical action recognition problem, this paper aims to estimate not only the scene category of a given video sequence, but also the spatial-temporal locations of the action instances. In recent years, many feature extraction schemes have been designed to describe various aspects of actions. However, due...
In this paper we propose a computational scheme for online incremental type classification of images, based on human assisted fuzzy similarity analysis. First of all, two main parameters from each image are extracted in the form of a center-of-gravity and a generalized volume of the image model.. Then their differences for each pair of images are taken as respective features F1 and F2, which serve...
This paper investigates the applicability of Gaussian processes (GP) classification for recognition of articulated and deformable human motions from image sequences. Using tensor subspace analysis (TSA), space-time human silhouettes (extracted from motion videos) are transformed to low-dimensional multivariate time series, based on which structure-based statistical features are calculated to summarize...
A novel statistical learning approach for automatic annotation of images is presented. A minimum probability of error annotation is feasible with our approach. Firstly, an image is represented as a bag of feature vectors by dividing the image into small blocks, from each of which a six-dimension feature vector is extracted. Secondly, we established the probabilistic formulation for automatic annotation...
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.