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.
nowadays, local features are widely used for content-based image retrieval. Effective feature selection is very important for the improvement of retrieval performance. Among various local feature extraction methods, Scale Invariant Feature Transform (SIFT) has been proven to be the most robust local invariant feature descriptor. However, the algorithm often generates hundreds of thousands of features...
In this paper, we propose a spatiotemporal salient objects-based approach for video retrieval. The spatiotemporal salient object is defined as the region sequence which is spatial salient and temporal continuous at the same time. As attention analysis is an effective mechanism for salient information selection, it provides a practical approach to narrow the semantic gap. Most existing methods extract...
Electroencephalogram (EEG) is one of the most important neuroelectrical signals and is often used to detect brain's neuroelectrical dysfunction. However, the analysis of the EEG signal and extraction of features from it has been a challenging task due to the complexity and variability. It is difficult to recognize different stages of the real-time sleeping EEG signal from single EEG signal automatically...
This paper proposes a new method for describing Dynamic Texture (DT). DT is an extension of still texture to temporal domain, which contains motion features and appearance features. An Extended Statistical Landscape Features (ESLF) method is proposed for DT description and recognition by characterizing the motion and appearance features. The proposed ESLF uses the ESLF histogram as the identifier...
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.