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 present a robust object tracking system capable of handling pose and scale variations. The system is based on adaptive sparse representation and dictionary learning. We focus on the problem of automatic tracking with no prior knowledge other than the location of the region to be tracked in the first frame, which could be located by a detector. The detected region, i.e., a bounding...
We present a method that automatically detects chewing events in surveillance video of a subject. Firstly, an Active Appearance Model (AAM) is used to track a subject's face across the video sequence. It is observed that the variations in the AAM parameters across chewing events demonstrate a distinct periodicity. We utilize this property to discriminate between chewing and non-chewing facial actions...
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.