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Current study performs a comparison of the contour inflection point selection methods according to the following criteria: probability of the correct selection, probability of the incorrect selection and an error in the coordinate estimation based on the results of model tasks. Results of the interpolation and differential methods and the method based on wavelet analysis of the contour inflection...
Pressure measurements within the chambers of the heart yield critical information for diagnosis and management of cardiac patients (∼92 million Americans), but cardiac catheterization procedure is invasive and expensive. Subharmonic aided pressure estimation (SHAPE) may be able to estimate intra-cardiac pressures noninvasively, if the optimum incident acoustic output (IAO) for SHAPE can be established...
Subharmonic aided pressure estimation (SHAPE) is based on the inverse relationship between the subharmonic amplitude of contrast microbubbles and the ambient pressure. A noninvasive ultrasound based pressure estimation procedure would be a major development in the diagnosis of portal hypertension and less invasive than the current hepatic venous pressure gradient (HVPG) measurement. The hypothesis...
The paper presents models and estimation algorithm of the air stream velocities in pneumatic material transport for supervisory and direct control layers of electromagnetic milling system. The algorithm uses redundant measurement system and identifies parameters of the first principle model to increase reliability of the measurements and to give rise of the fault detection system.
On the aged society coming soon, many studies have explored homecare technologies. In this work, the activities at home are captured by a panoramic camera located at the center of a living room, and then analyzed and classified into standing, walking, sitting, falling, and watching television. First, the background subtraction scheme accompanied with shadow removal, and morphological operators of...
The main contribution of this paper is the proposal of volume modeling of parathyroid gland. Multivariate generalized Gaussian distribution (Multivariate GGD) mixture is assumed. Random walk optimization algorithm is applied for the estimation of parameters. There are 800 synthetic test cases applied for the evaluation of algorithm properties. Example result for real SPECT data are also shown. The...
In this paper a new direct nonparametric estimation of the period and the shape of a periodic component in short duration signals is proposed and evaluated. Classical Fourier Transform (FT) methods lack precision and resolution when the duration of the signal is very short and the signal is noisy. The proposed method is based on the direct description of the problem as a linear inverse problem and...
Currently, the standard and regulations for specific absorption rate (SAR) testing of limb-worn devices specify the use of the flat phantom and the user's wrist is not considered. In this paper, the SARs for standard flat phantoms are calculated and compared with body shape phantom and anatomical human-body model. And we investigate the effect of wrist model during the SAR evaluation.
The paper addresses the problem of joint signal separation and estimation in a single-channel discrete-time signal composed of a wandering baseline and overlapping repetitions of unknown (or known) signal shapes. All signals are represented by a linear state space model (LSSM). The baseline model is driven by white Gaussian noise, but the other signal models are triggered by sparse inputs. Sparsity...
The paper presents a method to generate a large-scale 3D fundamental map from a running vehicle. To create an easy-to-use approach for frequent updates, we propose a system to utilize simultaneous localization and mapping (SLAM), which is robot mapping technology. In traditional methods, special machines or many manual operations cause higher mapping costs. The existing mobile mapping method (MMS)...
We address the problem of estimating human pose and body shape from 3D scans over time. Reliable estimation of 3D body shape is necessary for many applications including virtual try-on, health monitoring, and avatar creation for virtual reality. Scanning bodies in minimal clothing, however, presents a practical barrier to these applications. We address this problem by estimating body shape under clothing...
We propose a novel, practical solution for high quality reconstruction of axially-symmetric transparent objects. While a special case, such transparent objects are ubiquitous in the real world. Common examples of these are glasses, goblets, tumblers, carafes, etc., that can have very unique and visually appealing forms making their reconstruction interesting for vision and graphics applications. Our...
Many algorithms for the computation of correspondences between deformable shapes rely on some variant of nearest neighbor matching in a descriptor space. Such are, for example, various point-wise correspondence recovery algorithms used as a post-processing stage in the functional correspondence framework. Such frequently used techniques implicitly make restrictive assumptions (e.g., nearisometry)...
Estimating human pose, shape, and motion from images and videos are fundamental challenges with many applications. Recent advances in 2D human pose estimation use large amounts of manually-labeled training data for learning convolutional neural networks (CNNs). Such data is time consuming to acquire and difficult to extend. Moreover, manual labeling of 3D pose, depth and motion is impractical. In...
In this work we pursue a data-driven approach to the problem of estimating surface normals from a single intensity image, focusing in particular on human faces. We introduce new methods to exploit the currently available facial databases for dataset construction and tailor a deep convolutional neural network to the task of estimating facial surface normals in-the-wild. We train a fully convolutional...
This paper tackles the problem of estimating 3D human poses from given 2D landmarks, which is still an ill-posed problem. The existing works have successfully applied Active Shape Model approach to estimate 3D human poses, but the error is still high. In this paper, we propose an improved method by using the cascade of neural networks to make the estimated shape more alike to the ground truth shape...
Multi-view stereo relies on feature correspondences for 3D reconstruction, and thus is fundamentally flawed in dealing with featureless scenes. In this paper, we propose polarimetric multi-view stereo, which combines per-pixel photometric information from polarization with epipolar constraints from multiple views for 3D reconstruction. Polarization reveals surface normal information, and is thus helpful...
Area Sampling Frames are used for surveys including crop acreage and yield, forests, and natural resource inventories and are the foundation of the statistical program of the USDA National Agricultural Statistics Service (NASS) and many statistical survey programs around the world. An automated area frame stratification method was recently implemented into NASS operations, which is based on the objective...
In many practical problems, measurement noise data are often skewed, heterogeneous, or containing outliers. The Gaussian or even Student-t measurement noise settings are often not fit to the request of system. A novel EKF filtering algorithm for nonlinear discrete state-space models with skewed Student-t measurement noise is presented. The algorithm makes use of the method of Variational Bayes to...
We develop an Expectation-Maximization (EM) algorithm for the simultaneous tracking and shape estimation of a star-convex object based on multiple spatially distributed measurements. In order to formulate the problem within the EM framework, the unknown measurement sources on the object are modeled as hidden variables. As the measurement sources are continuous quantities, we develop a suitable discretization...
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