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.
We present a novel approach to automatically create efficient and accurate object detectors tailored to work well on specific video surveillance cameras (specific-domain detectors), using samples acquired with the help of a more expensive, general-domain detector (trained using images from multiple cameras). Our method requires no manual labels from the target domain. We automatically collect training...
In this paper, a macroblock classification method is proposed for various video processing applications involving motions. Based on the analysis of the Motion Vector field in the compressed video, we propose to classify Macroblocks of each video frame into different classes and use this class information to describe the frame content. We demonstrate that this low-computation-complexity method can...
Surveillance videos are often compressed for transmission or storage. It is desirable to be able to perform automatic event detection in the compressed domain directly. In this paper, we investigate the use of motion trajectories for video activity detection in the compressed domain. We show that it is possible to extract reliable motion trajectories directly from compressed H.264 video streams. To...
In this paper we address the problem of unsupervised discovery of action classes in video data. Different from all existing methods thus far proposed for this task, we present a space-time link analysis approach which matches the performance of traditional unsupervised action categorization methods in a standard dataset. Our method is inspired by the recent success of link analysis techniques in the...
We formalize data scaling classification (DSC) as a technique to trade the accuracy of classification with the network transmission load in stream analysis frameworks. We apply the proposed data scaling approaches to ECG classification in remote health monitoring systems. Experimental results show satisfactory resource savings for small amounts of utility degradation (e.g., 33% of bandwidth saving...
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.