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.
Many applications in media production need information about moving objects in the scene, e.g. insertion of computer-generated objects, association of sound sources to these objects or visualization of object trajectories in broadcasting. We present a GPU accelerated approach for detecting and tracking salient features in image sequences and we propose an algorithm for clustering the obtained feature...
We present a method to group trajectories of moving objects extracted from real-world surveillance videos. The trajectories are first mapped into a low dimensionality feature space generated through linear regression. Next the regression coefficients are clustered by a Gaussian mixture model initialized by K-means for improved efficiency. The model selection problem is solved with Bayesian information...
The task of clustering multivariate trajectory data of varying length exists in various domains. Model-based methods are capable of handling varying length trajectories without changing the length or structure. Hidden Markov models (HMMs) are widely used for trajectory data modeling. However, HMMs are not suitable for trajectories of long duration. In this paper, we propose a similarity based representation...
The paper describes a general platform for live video analysis. The first stage of the platform is to build a topological scene description by learning the location of nodes (i.e. zones), which are called points of interest. There are two kinds of points of interest, the entry-exit zones (areas where moving object appear and disappear in the scene) and the stopping zones (areas where the moving objects...
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.