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Many sensor network applications are tightly coupled with the geometric environment where the sensor nodes are deployed. The topological skeleton extraction has shown great impact on the performance of such services as location, routing, and path planning in sensor networks. Nonetheless, current studies focus on using skeleton extraction for various applications in sensor networks. How to achieve...
We study the anchor-free localization problem for a large-scale sensor network with a complex shape, knowing network connectivity information only. The main idea follows from our previous work in which a subset of the nodes are selected as landmarks and the sensor field is partitioned into Voronoi cells with all the nodes closest to the same landmark grouped into the same cell. We extract the combinatorial...
Distributed active sensing is a new sensing paradigm, where active sensors as illuminating sources and passive sensors as receivers are distributed in a field, and collaboratively detect objects of interest. Obstacle discovery concerns with the problem of detecting the presence and determining the location of obstacles with many applications in robot navigation, object tracking, and surface and/or...
To analyze time-varying data sets, tracking features over time is often necessary to better understand the dynamic nature of the underlying physical process. Tracking 3D time-varying features, however, is non-trivial when the boundaries of the features cannot be easily defined. In this paper, we propose a new framework to visualize time-varying features and their motion without explicit feature segmentation...
Symbols are frequently used to represent data objects in visualization. An appropriate contrast between symbols is a precondition that determines the efficiency of a visual analysis process. We study the contrast between different types of symbols in the context of scatterplots, based on user testing and a quantitative model for symbol contrast. In total, 32 different symbols were generated by using...
In this paper, we study the problem of recognizing an unknown probability density function from one of its sample which is of interest in signal and image processing or telecommunication applications. By opposition with the classical Kolmogorov-Smirnov method based on empirical cumulative functions, we consider histogram estimators of the density itself built from our data. Those histograms are generated...
In this paper, we present a new algorithm of snakes with geometric prior. A method of shape alignment using Fourier coefficients is introduced to estimate the Euclidean transformation between the evolving snake and a template of the searched object. This allows the definition of a new field of forces making the evolving snake to have a shape similar to the template one. Furthermore, this strategy...
Multi-capacities ambulance location model (MCAL) is a different type of capacitated location model compared with ambulance location/relocation model existed. It considers three different types of capacities: traveling distance, address point (population) and EMS incident locations, into one model to solve the set covering of ambulance service area location problem. MCAL is not only a deterministic...
Spatial structure of objects is an important feature of images and making use of this feature properly is very important for the user in the retrieval system. However, only a third of the existing image retrieval systems use spatial features and those features are low precision features which are variant to rotation and shift. In this paper, a polygon-based spatial feature model is proposed to describe...
Pattern identification from multisensor time series is an important problem in many measurement, detection, and monitoring related applications. This paper introduces a generic approach to detect varying-length patterns and identify their class using predefined templates. In reality, the measured phenomena representing the same class can occur in slightly different ways which makes the resulting patterns...
In architectural and mechanical engineering, man-made CAD models often have some prominent contours and regular shapes. These features are important to the visual perception. Traditional mesh simplification methods are not very suitable for this kind of models because in the simplified results some important mini structures and shape regularities are always missed. In this paper, we propose a new...
The paper presents an evaluation of four clustering algorithms: k-means, average linkage, complete linkage, and Wardpsilas method, with the latter three being different hierarchical methods. The quality of the clusters created by the algorithms was measured in terms of cluster cohesiveness and semantic cohesiveness, and both quantitative and predicate-based similarity criteria were considered.Two...
This paper describes a multi-seeds mesh growing and flat portions first growing algorithm that takes as input an unorganized set of points on an unknown manifold, and produces as output an approximate surface. A priority driven strategy for mesh growing is then used to sweep the advance front ahead in an effective way. The method makes no assumption regarding the points, and the main contributions...
How to control bottom water energy reasonably and effectively of bottom-water reservoir is puzzling Field Engineer until now. The key technique of development for bottom-water reservoirs is to depress or control water cone, prolong water free production period as much as possible. In order to settle the question, this paper, based on static mechanism and kinetic equation of underground fluid, the...
Reliable shape modeling and clustering of white matter fiber tracts is essential for clinical and anatomical studies that use diffusion tensor imaging (DTI) tractography techniques. In this work we present a novel scheme to model the shape of white matter fiber tracts reconstructed from DTI and cluster them into bundles using Fourier descriptors. We characterize a tract's shape by using Fourier descriptors...
This paper addresses recent advances in computational tools for analysis of molecular imaging, medical imaging, and mass spectrometry data in cancer and cardiovascular diseases. These recently developed methods based on the principles of linear prediction, geostatistics, and fuzzy-set theory appear to be very useful sources of information for understanding the interactions and behaviors of complex...
This paper proposes a highly robust method for face recognition. Techniques introduced in this work are composed of two stages. Firstly, the feature of face is to be detected by the combined of trace transform and fast active contour. Then, in the second stage, the Hausdorff distance and modified shape context are employed to measure and determine of similarity between models and test images. Our...
We demonstrate composable volumetric lenses as interpretational tools for geological visualization. The lenses provide a constrained focus region that provides alternative views of datasets to the user while maintaining the context of surrounding features. Our rendering method is based on run-time composition of GPU shader programs that implement per-fragment clipping to lens boundaries and surface...
We present a hybrid user interface and gesture-based direct visual editing techniques for quick and rough object creation and manipulation in three-dimensional (3D) virtual environments (VEs). The user interface includes a novel table-prop to resemble an architect's physical workbench. A tracked pinch glove and a stylus pen provide both rough and fingertip level precise spatial input. For quick placement,...
This paper describes development of a haptic interface using a laser range finder. The system consists of a laser range finder, a 1 degree-of-freedom haptic apparatus and a computer. The haptic apparatus can generate a reaction force based on a distance to a remote object that is measured by the laser range finder. A user can feel the shape of a remote object by holding this interface and pointing...
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