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In this paper, we perform 3-Dimensional (3D) clustering based on the Outdoor-to-Indoor (O2I) wideband 3D multiple-input-multiple-output (MIMO) channel measurement at 3.5 GHz. Clusters are identified by KPowerMeans algorithm. Based on analysis on clustering results, we modified the definition of Multiple component distance (MCD) to split the bounding of azimuth and elevation, which can obtain larger...
With rapid advances in technology and connectivity, the capability to capture data from multiple sources has given rise to multiview learning wherein each object has multiple representations and a learned model, whether supervised or unsupervised, needs to integrate these different representations. Multiview learning has shown to yield better predictive and clustering models, it also is able to provide...
This paper proposes a visual approach based on a RGB/HSV tag to precise and autonomous landing of unmanned aerial vehicles (UAV). The proposed tag is correctly identified by an algorithm divided in four stages: hue filtering, clustering, matching and center location. The first stage is based on fuzzy matching and highlights the pixels with similar colors to the searched pattern, while ignores the...
We propose a video graph based human action recognition framework. Given an input video sequence, we extract spatio-temporal local features and construct a video graph to incorporate appearance and motion constraints to reflect the spatio-temporal dependencies among features. them. In particular, we extend a popular dbscan density-based clustering algorithm to form an intuitive video graph. During...
The visual navigation on the lunar surface is a natural way to alleviate the accumulated error raised by the inertial navigation device. However, it is difficult to find distinctive landmarks for effective visual navigation due to the similar and textureless terrains on the lunar surface. In this paper, a novel algorithm is proposed to solve such a problem. Firstly, the local invariant features extract...
In this work different clustering approaches are investigated in the millimeter-wave (mm-W) frequency band from measurements and simulations. Multipath Component (MPC) parameters have been extracted from both measurements and simulations using RiMAX. Following this step, several clustering techniques such as visual inspection, K-means, and multipath component distance (MCD) were implemented and analyzed...
In this paper, we present a novel method that can produce a visual description of a landmark by choosing the most diverse pictures that best describe all the details of the queried location from community-contributed datasets. The main idea of this method is to filter out non-relevant images at a first stage and then cluster the images according to textual descriptors first, and then to visual descriptors...
Aesthetic tendency discovery is a useful and interesting application in social media. This paper proposes to categorize large-scale Flickr users into multiple circles. Each circle contains users with similar aesthetic interests (e.g., landscapes or abstract paintings). We notice that: 1) an aesthetic model should be flexible as different visual features may be used to describe different image sets,...
Scene detection is a fundamental tool for allowing effective video browsing and re-using. In this paper we present a model that automatically divides videos into coherent scenes, which is based on a novel combination of local image descriptors and temporal clustering techniques. Experiments are performed to demonstrate the effectiveness of our approach, by comparing our algorithm against two recent...
Synchrophasors are the state-of-the-art measuring sensors that sense voltage, current, or frequency with high data rate. This paper presents an approach to analyze the streaming smart-grid data generated by synchrophasors. A novel unit-circle representation is used to visualize the real-time phasor data. A Density based clustering (DBSCAN) method is proposed to cluster the phasor data to detect bad-data...
High spatial resolution satellite imagery has become an important source of information for geospatial applications. Automatic segmentation of high-resolution satellite imagery is useful for obtaining more timely and accurate information. In this paper we introduce a new approach for automatic image segmentation into different regions (corresponding to various features of texture, intensity, and color)...
Most of the existing methods for generating a visual dictionary SIFT based on local characteristics, and adopt the common K-means clustering method to get the visual dictionary. But when the image vector dimension of the local feature is growing higher, the vector distribution of the local characteristics becomes sparse, resulting in the high correlation distance between the image vectors and reducing...
Measure Projection Analysis (MPA) method based on EEGLAB and Matlab Toolbox is used to analyze the projections of brain signal sources that are responsible for the measured potentials at the scalp electrodes. These projections are based on probabilistic multi subject algorithm abandoning the notion of distinct independent component clusters. It examines voxel by voxel for brain regions having event...
Slum reallocation is one of the major tasks of the Indian government to make India a slum free country and provide everyone with an appropriate accommodation. Reallocation part of slum cluster was a very tedious & completely manual and time consuming process involving complex calculations with various loop holes for error. In order to eradicate this problem and better functioning, this paper focuses...
Daily increase in the number of available video material resulted in significant research efforts for development of advanced content management systems. First step towards the semantic based video indexing and retrieval is a detection of elementary video structures. In this paper we present the algorithm for finding shot boundaries by using spectral clustering methods. Assuming that a shot boundary...
In this paper, we introduce a novel visualization method which allows people to explore, compare and refine the major communities in a large network. We first detect major communities in a network using data mining and community analysis methods. Then, the statistics attributes of each community, the relational strength between communities, and the boundary nodes connecting those communities are computed...
Clustering is often a first step when trying to make sense of a large data set. A wide family of cluster analysis algorithms, namely hierarchical clustering algorithms, does not provide a partition of the data set but a hierarchy of clusters organized in a binary tree, known as a dendrogram. The dendrogram has a classical node-link representation used by experts for various tasks like: to decide which...
With the explosive growth of Web and tremendous development of digital image processing technologies, the applications of Web image have attracted much attention, such as the Web image retrieval. Since the Web images are often with some related text tags, making use of both visual and textual features of Web image will help improving the accuracy of the Web image clustering. Researches show that Web...
A superpixel is an image patch which is better aligned with intensity edges than a rectangular patch. Superpixels are perceptually consistent units which carry more information than pixels and adhere well to image boundaries. Nowadays superpixels are widely used for segmentation in computer vision and biomedicai applications. There are many approaches to generate superpixels such as SLIC, QuickShift,...
The aim of clustering is to discover the clusters based on the similarity features of objects. The present algorithm of visual access tendency (VAT) can access an exact number of clusters by its VAT image. The VAT image displays the squared shaped dark blocks along the diagonal; number of cluster information is accessed by counting the number of obtaining square blocks. Other extended versions are...
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