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In this paper, we propose a novel relay selection scheme based on geographical information, aiming to minimize the symbol error probability (SEP) for wireless ad hoc relay networks. The proposed scheme utilizes only the source-relay and relay-destination distances as selection criteria to choose the best relay. In particular, such geographical information is often available during network initialization...
In this paper, we propose a novel and efficient relay selection protocol based on geographical information for cluster-based cooperative wireless sensor networks (WSNs). Multihop transmission is realized by concatenation of single cluster-to-cluster hops, where each cluster-to-cluster scheme forms the simplified cooperative network that consists of a single source- destination pair and a set of available...
Clustering is a popular tool for exploratory data analysis. One of the major problems in cluster analysis is the determination of the number of clusters in unlabeled data, which is a basic input for most clustering algorithms. In this paper we investigate a new method called DBE (dark block extraction) for automatically estimating the number of clusters in unlabeled data sets, which is based on an...
This work presents a robust method to detect blob and fit its contour in image. Previous methods for blob detection and delineation were either liable to fail with outliers and noise or computationally expensive. By incorporating the prior information of the region-of-interest and introducing the concept of the kernel MSER, the modified MSER detection method can detect the unique blob which is the...
Given a pairwise dissimilarity matrix D of a set of objects, visual methods such as the VAT algorithm (for visual analysis of cluster tendency) represent (D macr )as an image (D macr ) where the objects are reordered to highlight cluster structure as dark blocks along the diagonal of the image. A major limitation of such visual methods is their inability to highlight cluster structure in 1(D macr...
This paper proposes a novel algorithm for categorization of action video sequences using unsupervised dual clustering. Given a video database, we extract motion information of actions and perform nonlinear dimensionality reduction for addressing both the high dimensionality of silhouette features and non-linearity of articulated human actions. A k-means clustering is first performed on frame-wise...
This paper presents a weighted extended Kalman filter (WEKF) for target tracking in wireless sensor networks, where the location estimation is formulated as a weighted least squares (WLS) problem by taking weights of the local estimates based on the reliability of distance estimation and the WLS problem is solved in an iterative, decentralized manner based on the WEKF. We adopt a message passing (MP)...
In this paper, we propose a modified incremental subgradient (MIG) algorithm with a variable step size for positioning and tracking a target in wireless sensor networks. The proposed positioning scheme formulates location estimation as a nonlinear least-squares problem using the received signal strength, and then applies the MIG algorithm with a fixed step size to solve the problem. This scheme can...
In this paper, we propose a weighted incremental subgradient (WIG) algorithm for positioning and tracking in wireless sensor networks. We formulate the location estimation of a target as a weighted least squares (WLS) problem by taking weights of the local estimates based on the reliability information of distance estimation, and then solve the WLS problem in an iterative, decentralized manner using...
In this paper we present a novel framework for learning contextual motion model involving multiple objects in far-field surveillance video and apply the learned model to improving the performance of objects tracking and abnormal event detection. We represent trajectory of multiple objects by a 3D graph G in x,y,t, which is augmented by a number of spatio-temporal relations (links) between moving and...
This paper proposes an approach called dasiastructure-based spectral clusteringpsila to identify clusters in motion time series for sequential pattern discovery. The proposed approach deploys a dasiastatistical feature-based distance computationpsila for spectral clustering algorithm. Compared to traditional spectral clustering approaches, in which the similarity matrix is constructed from the original...
Time-of-flight range sensors have error characteristics which are complementary to passive stereo. They provide real time depth estimates in conditions where passive stereo does not work well, such as on white walls. In contrast, these sensors are noisy and often perform poorly on the textured scenes for which stereo excels. We introduce a method for combining the results from both methods that performs...
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