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.
With the exponential growth of surveillance videos, conference videos and sports videos, videos with static cameras present an unprecedented challenge for high-efficiency video coding technology. The existing schemes developed for these videos mostly encode the background as the long-term reference (LTR) to further improve the coding efficiency. However, since the bit allocation of the long-term background...
As the translational motion model used in recent video coding standards cannot represent the complex motion such as rotation and zooming well, a simple local affine motion compensation framework supporting multiple reference frames is proposed in this paper to characterize the complex motion. Besides, since the commonly used fast motion estimation for affine motion model is still quite complex, a...
Detecting and segmenting moving object is an important subject in computer visual analysis. Firstly, the algorithms of detecting moving target from static background in video sequences are discussed in this paper. Secondly, as the inter-frame subtraction can't detect moving object accurately and mixture Gaussian models can't solve the problems such as ghost, shadow and real-time application, a new...
Detecting and segmenting moving object is an important subject in computer visual analysis. Firstly, this paper discusses algorithms of detecting moving target from static background in video sequences. Secondly, as the existing mixture Gaussian models can't solve the problems such as ghost and real-time application, a new method based on moving edge detection of difference between adjacent frames...
With the development of Multimedia Network Technology and the rapid increase of image application, Content-based Image Retrieval (CBIR) becomes the most active one in multimedia information retrieval field. One of the key issues is how to construct effective organization and index to enhance image retrieval speed. Clustering is a kind of effective method. This paper presents a modified fuzzy C-means...
How to use low-level image features such as color, texture, shape, spatial relationship etc. logically in retrieval is an important problem for both retrieval system and users. An image retrieval method based on the four lands of image low-level features is proposed in this paper. According to image texture characteristic, a land of image feature statistic is defined. By using feature weight assignment...
In CBIR (content-based image retrieval), image has various inherent features which reflect its content such as color, texture, shape, spatial relationship features etc. How to organize and utilize these features effectively and improve the retrieval performance is a valuable research topic. One of the key issues in image retrieval based on combined features is how to assign weight to different features...
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.