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.
This paper presents an algorithm for object localization and segmentation. The algorithm uses machine learning, and statistical and combinatorial optimization tools to build a tracker that is robust to noise and occlusions. The method is based on a novel energy formulation and its dual use for object localization and segmentation. The energy uses kernel principal component analysis to incorporate...
As an active topic in pattern recognition, the graph spectral is applied in clustering and segmentation. But issues in the analysis to image, especially the texture image, could not been retrieved till now. In this paper, we present a novel texture analysis method, which introduces graph spectral theory into the field of texture image analysis. At first, the image is partitioned into several sub images...
The methods presented in this paper aim at detecting and recognizing players on a sport-field, based on a distributed set of loosely synchronized cameras. Detection assumes player verticality, and sums the cumulative projection of the multiple views' foreground activity masks on a set of planes that are parallel to the ground plane. After summation, large projection values indicate the position of...
We introduce principal-channels for cutting out objects from an image by one-sided scribbles. We demonstrate that few scribbles, all from within the object of interest, are sufficient to mark it out. One-sided scribbles provide significantly less information than two-sided ones. Thus, it is required to maximize the use of image-information. Our approach is to first analyze the image with a large filter...
This paper presents an unified framework for fast interactive segmentation of natural images using the image foresting transform (IFT) - a tool for the design of image processing operators based on connectivity functions (path-value functions) in graphs derived from the image. It mainly consists of three tasks: recognition, enhancement, and extraction. Recognition is the only interactive task, where...
This article proposes a new characteristic-based image mosaic algorithm that used the granular computing theory. Firstly, establish a granular computing model of the image waiting to be spliced to obtain the image's edge segmentation; Secondly, extract the characteristic points in the edge graph, then carry on the related operation to these characteristic points to find matching characteristic points,...
This paper presents a new method for building rooftop detection from aerial images. In our approach, we extract useful building location information from the generated disparity map to segment the interested objects and consequently reduce unnecessary line segments extracted in the low level feature extraction step. Hypothesis selection is carried out by using an undirected graph, in which close cycles...
In this paper a region-based image indexing and retrieval (RBIR) algorithm is presented. As a basis for the indexing, a novel spectral segmentation approach using random walks on graphs is introduced. Based on the extracted regions, characteristic features are estimated using color and texture information. The focus of this study is to improve the capture of regions so as to enhance indexing and retrieval...
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.