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This paper presents a solution to the Projective Structure from Motion (PSfM) problem able to deal efficiently with missing data, outliers and, for the first time, large scale 3D reconstruction scenarios. By embedding the projective depths into the projective parameters of the points and views, we decrease the number of unknowns to estimate and improve computational speed by optimizing standard linear...
We describe the implementation of a single-phase estimation algorithm for phasor measurement unit (PMUs) compliant with the IEEE C37.118.1-2011 standard. It consists of three stages: The fist one is a bandpass FIR filter that allows the relaxation of the requirements of the following stages. The second one is a digital extension on state-space of the pseudo-linear enhanced phase locked loop (PL-EPLL)...
The optimal filtering problem for non-stationary stochastic continuous-time observation models is considered. It is known that the problem solution can be found using both the Duncan-Mortensen-Zakai equation and the robust Duncan-Mortensen-Zakai equation. In this paper the special form of the robust Duncan-Mortensen-Zakai equation, where the drift, diffusion, and potential functions are expressed...
Allowing for a priori optimization of the robot manipulation to improve the performance in the unmanned environment, it is critical for the augmented reality system to estimate the attitude of point clouds in model reconstruction. The estimation of planar parameter is not always faithful for point cloud fitting, because the gross errors and outliers are not considered in by the traditional plane fitting...
An intuitive approach is proposed for outlier recognition among 2D point correspondences. The main novelty of the proposed method is the exploitation of feature point topology provided by Delaunay triangulation. The solution obtained by minimizing an energy originated from neighboring correspondences in order to remove incorrectly paired points. Assuming local, approximately rigid structures, it is...
The two-stage Kalman filter was proposed with the objective to avoid bias when the system is in presence of input signals. A common technical difficulty in this technique is that the dynamics of input signal is always unknown whereas the optimality of such filter can only be achieved with sufficient priori knowledge (i.e., known dynamics and statistics). Unbiased minimum-variance filter is capable...
This paper presents a new scheme of Dynamic State Estimation (DSE) employing three parameter exponential smoothing technique to depict the time evolution of the power system states at the prediction step. To resolve the filtering problem it utilizes the efficient Extended Kalman Filter (EKF). The proposed scheme of DSE has been tested on IEEE 5-bus, 14-bus, 30 bus and 57 bus test systems. The test...
The estimation of battery state-of-charge (SOC) is crucial for the safety and reliability of electric vehicles. This paper develops an auxiliary particle filter based on a Markov-chain Monte-Carlo (MCMC) method. Compared with the standard particle filter, it improves the estimation accuracy by incorporating auxiliary sampling and enhances its robustness by using MCMC resampling. Simulation results...
Apparent age estimation from face image has attracted more and more attentions as it is favorable in some real-world applications. In this work, we propose an end-to-end learning approach for robust apparent age estimation, named by us AgeNet. Specifically, we address the apparent age estimation problem by fusing two kinds of models, i.e., real-value based regression models and Gaussian label distribution...
An efficient foreground detection algorithm is presented in this work to be robust against consecutively illuminance changes and noise, and adaptive with dynamic speeds of motion in the background. The scene background is firstly modeled by a novel algorithm, namely Neighbor-based Intensity Correction, which identifies and modifies motion pixels extracted from the difference of the background and...
The so-called direct SLAM methods have shown an impressive performance in estimating a dense 3D reconstruction from RGB sequences in real-time [1], [2], [3]. They are based on the minimization of an error function composed of several terms that account for the photometric consistency of corresponding pixels and the smoothness and the planarity priors on the reconstructed surfaces. In this paper we...
A task of time delay estimation for wideband signals in non-Gaussian environment is considered. An approach based on application of robust DFT for obtaining spectrum estimates of sensor signals for observation interval is proposed and shown to perform better than conventional approaches for noise modeled as symmetric α-stable process.
There has been an exponential growth in brain mapping studies in the past decade using functional MRI (fMRI). Apart from simple fMRI studies from a single site (scanner), multi-site studies are gaining great attention, as it has the potential to provide more data for brain mapping studies, thereby increasing the statistical power of the brain mapping studies. Major limitations with the multi-center...
This paper proposes the use of Synchronous Ethernet in networks with multiple paths for the synthesis of a precise frequency reference for distributed measurement systems. The paper presents novel approach based on a Kalman filter with outlier identification and removal followed by a linear quadratic regulator (LQR). The algorithm, to be implemented within a network element, is able to synthetize...
This paper presents two new methods for robust parameter estimation of mixtures in the context of MR data segmentation. The head is constituted of different types of tissue that can be modeled by a finite mixture of multivariate Gaussian distributions. Our goal is to estimate accurately the statistics of desired tissues in presence of other ones of lesser interest. These latter can be considered as...
Radio astronomy observations suffer from strong interferences that need to be blanked both in the time and frequency domains. In order to achieve real-time computations, interference detection is made by simple thresholding. The threshold value is linked to the mean estimation of the power of clean observed data that follows a χ2 distribution. Spurious values insensitivity is obtained by replacing...
In this paper, we propose a new error criteria for determining the optimal multi-channel model system. The error criteria is based on assuming that the probability density function of the resulted error signal is t-distributed with α degrees of freedom. A small weighting factor is assigned for large amplitude signal portion parts and large weighting factor is used for small amplitude signal portion...
Decision based non-linear filtering is widely used for the removal of impulsive noise. Various robust statistical estimators of scale are in use for determining the threshold of the filtering process. Real-time filtering requires this estimation to be computationally efficient and realizable within the system constraints. This paper proposes the use of Interquartile range (IQR) for filtering impulsive...
In rough set approaches, decision rules are induced from a given data table showing the relation between attribute values and classes of objects. The induced decision rules are used for the classification of new objects by their attribute values. However, some of new objects do not match any decision rule conditions because the given data table does not always include all possible patterns. In those...
Methods based on Local Binary Patterns have been used successfully in a wide range of texture classification tasks. A restriction shared by all methods based on Local Binary Patterns is the high sensitivity to signal scale. In recent work we presented a general framework for scale-adaptive computation of Local Binary Patterns, improving the accuracy in texture classification scenarios involving varying...
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