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.
Discovering semantic knowledge is significant for understanding and interpreting how people interact in a meeting discussion. In this paper, we propose a mining method to extract frequent patterns of human interaction based on the captured content of face-to-face meetings. Human interactions, such as proposing an idea, giving comments, and expressing a positive opinion, indicate user intention toward...
Recently, researchers are paying more attention to 3D model classification due to its useful applications in multimedia, computer graphics, and so on. Although there exist a number of approaches to classify 3D models, few of them consider the prior knowledge during the process of 3D model classification. In this paper, we propose a new framework called knowledge based cluster ensemble which incorporates...
A novel approach for 3D motion capture data retrieval based on the Hierarchical Self Organizing Map (HSOM) is proposed. Given a query motion sequence, our goal is to search for all the similar motions from a database. Specifically, a feature vector based on the distribution of the human motion data is first extracted from each motion sequence in the database. Then, Singular Value Decomposition (SVD)...
Due to the rapid development of motion capture technology, more and more human motion databases appear. In order to effectively and efficiently manage human motion database, human motion classification is necessary. In this paper, we propose an ensemble based human motion classification approach (EHMCA). Specifically, EHMCA first extracts the descriptors from human motion sequences. Then, singular...
In this paper, we propose a novel 3D human motion sequence retrieval method based on the similarity of the motion data distribution. First, for each motion sequence in the database, the self-organizing maps (SOM) clustering algorithm is adopted to partition the frames into different classes to get the associated class reference vectors. Then given a query motion, probabilistic principal component...
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.