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Subspace clustering is one of the active research problem associated with high-dimensional data. Here some of the standard techniques are reviewed to investigate existing methodologies. Although, there have been various forms of research techniques evolved recently, they do not completely mitigate the problems pertaining to noise sustainability and optimization of clustering accuracy. Hence, a novel...
In order to reduce the false matching rate and matching time, an improved algorithm based on RANSAC-SIFT was proposed. The feature points were extracted by SIFT algorithm firstly. Then most of the mismatching points were eliminated according to the constraints that matching distances tend to be consistent. Finally the remaining points were regarded as pre matching points for achieve fine matching...
The feasibility of large-scale decentralized networks for local computations, as an alternative to big data systems that are often privacy-intrusive, expensive and serve exclusively corporate interests, is usually questioned by network dynamics such as node leaves, failures and rejoins in the network. This is especially the case when decentralized computations performed in a network, such as the estimation...
This paper deals with features of robust two-degree-of-freedom system assigned for stabilization of information and measuring systems operated on the ground vehicles in difficult conditions accompanied by influence of the parametric and coordinate disturbances. The optimization criterion and state space model of the augmented plant are derived. The design procedure of robust system for stabilization...
Both tracking and robust performance are important issues in control engineering. Tracking performance represents how precise the actuator can follow the reference, while robust performance shows how far the actuator can function properly when plant uncertainty and disturbance appear. This works assess both tracking and robust performance of two popular control algorithms i.e Sliding Mode Control...
Interferometrie Synthetic Aperture Radar (InSAR) can derive accurate 3D information with image acquiring all time and all weather. But the accuracy of derived 3D information is heavily determined by the length of perpendicular baseline. We know that the longer baseline is, the more accurate Digital Elevation Model (DEM) can be derived in condition of other parameters are the same. Meanwhile the phase...
The number of vehicles in cities has increased dramatically due to rapid economic development. However, the infrastructure for accommodating these vehicles has grown relatively slow. Alleviating the pressure on the urban transport system and solving the ‘parking difficulty’ problem have thus become hot topics recently. In this paper, an intelligent parking system based on geomagnetic field variations...
Sequential learning-based pattern classification aims at providing more accurate labeled maps by adding an extra step of classification using an augmented feature vector. In this paper, we evaluated the robustness of Optimum-Path Forest (OPF) classifier in the context of land-cover classification using both satellite and radar images, showing OPF can benefit from sequential learning theoretical basis.
Random Forests and their many variations developed to one of the most successful instruments to automatically analyse image data. One of the most crucial parts is the definition and selection of node tests within the individual trees, which among other things allow for trade-offs between accuracy and computational load. This paper discusses several different approaches to test creation and compares...
This paper addresses the problem of person re-identification and its application to a real world scenario. We introduce a retrieval system that helps a human operator in browsing a video content. This system is designed for determining whether a given person of interest has already appeared over a network of cameras. In contrast to most of state of the art approaches we do not focus on searching the...
We propose a real-time method for 3D head pose estimation from RGB-D sequences. Our algorithm relies on a Random Forest framework that is able to regress the head pose at every frame in a temporal tracking manner. Such framework is learned once from a generic dataset of 3D head models and refined online to adapt the forest to the specific characteristics of each subject. Through the qualitative experiments...
Computer and telecommunications advances in the last years allowed new distributed applications developments. In this context, time synchronization is a very important issue. Many industrial sectors, such as financial and power, need to achieve high time accuracy. The IEEE 1588–2008 standard [1] defines the second version of PTP, designed to archive clock accuracy in the sub-microsecond range. Previous...
Motion errors are inevitably introduced when data are acquired and considerably degrade the image quality in terms of geometric resolution, radiometric accuracy and image contrast, especially in high resolution spotlight synthetic aperture radar (SAR) imagery. In this paper, we describe a weighted contrast enhancement autofocus algorithm that is based on spatially variant model and adopts a mean square...
Traditional Support Vector Regression (SVR) Machine acts as approximating a regression function. This paper, however, proposes a novel multi-class classification approach based on the SVR framework, called Support Vector Regression Machine with Consistency (SVRC). The contributions of this paper are: (1) To implement multi-class classification task, were place the margin term with its l1 norm in the...
This paper proposes a new method for image registration by combining SURF and FREAK. SURF can extract robust feature points, and the topology of FREAK descriptor has strong ability of regional description. First, feature points of images are extracted by SURF, and described by FREAK descriptor. Then descriptors are roughly matched through the ratio of the closest neighbor and second closest one. Second,...
In this paper, we propose a novel method for point clouds registration. In point clouds, there always exist a large number of surfaces with low curvatures. Let the surface locate in an OXYZ coordinate system, if we rotate the mean normal of the surface parallel with the Z axis, the 3D surface can be projected to 2D image via orthographic projection. Then we can detect and describe SIFT features in...
This paper presents two new modelling algorithms that was recently added to the commercially available GRASP software package for electrically large antenna and scattering problems. In particular, a new higher-order multilevel fast multipole solver (HO-MLFMM) provides very high simulation accuracy while requiring significantly less memory and CPU time than the commonly available low-order MLFMM. At...
this paper presents a new approach to extract image features for texture classification. The extracted features are obtained by a dominant-completed modeling of the traditional local binary pattern (LBP) operator, which is robust to image rotation, grey scale changing and insensitive to noise and histogram equalization. The main idea of this texture classification approach is that a dominant center...
With the development of computer vision technology, many researches about feature detectors and descriptors have been published in the last decades. In order to explore what kind of approaches are appropriate for unmanned aerial vehicle (UAV) onboard video processing, the popular feature detectors and descriptors are analyzed and combined with each other. Three practical videos captured in indoor...
The paper is aimed to control design of uncertain linear multivariable plants in conditions of quantized output and external disturbances. Control law synthesis is based on the consecutive compensator method. Obtained algorithm provides tracking error of quantized output for the reference signal with fixed accuracy. Accuracy range depends on the quantization step and disturbances bounds. There are...
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