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In a low signal / noise ratio, shape deviation of detected signals causes them pass. The task of neutralization of this effect is classified as actual one. In active control systems it is proposed to solve the task through result tracing operation of reactions comparison for controlled and reference objects on sounding effects. The most probable one is selected according to similarity degree of possible...
This paper is aimed at presenting a new algorithm for multi-path interference resolutions under mirror-based full 3D capture using a single correlation-based ToF camera. Our algorithm does not require additional captures or device modifications, and resolves the interference using a single ToF sensing that is also used for the 3D reconstruction as well. Evaluations with real images prove the concept...
In this research, a new technique For Content Based Image Retrieval (CBIR) with contrast enhancement using multi-feature and multi kernel Support Vector Machine (SVM) method. Color moment (CM), Auto Correlogram (AC), Discrete Wavelet Transform (DWT), Gabor Filter (GF) features are proposed. We extended the previous work which used binary SVM classifier and color features. First of all take a query...
We studied tongue shapes extracted from X-ray films which were taken during the process of mandarin Chinese articulation. Through factor analysis, we built an eight-parameter-driven tongue articulation model. This study reveals that the front of the tongue has large horizontal movement; the blade of the tongue has large vertical movement; whereas the back, as well as the root, of the tongue has small...
In this paper, the problem of estimating the motion and shape parameters from the infrared signature of precession object is addressed. To limit the scope of this work, only objects with shape of flat-plane, cone, cylinder, cone-cylinder combination are considered. Different from the current research, the parameter estimating is based on signal modeling. First, a signal model is proposed to approximate...
In this paper, road roughness model for the right and the left tracks are constructed by utilizing two methods. In the first method, from time-domain measurements the empirical auto and cross-power spectral densities of the left and the right tracks are estimated by using the Welch method. Next, the road roughness is decomposed into three stochastically independent random processes and the linear-shape...
Driving behaviour prediction is a challenging problem due to the nonlinearity of human behaviour. Linear and nonlinear techniques have been used to solve this problem, and they provide good results presented in the performance of the current autonomous cars. However, they lack the ability to adapt to abruptness that happens because of the human factor. In this paper, we introduce a method to extract...
Research on iris recognition have observed that iris texture has inherent radial correlation. However, currently, there lacks a deeper insight into iris textural correlation. Few research focus on a quantitative and comprehensive analysis on this correlation. In this paper, we perform a quantitative analysis on iris textural correlation. We employ steering kernels to model the textural correlation...
This article concerns an autocorrelation algorithm for determining a pulse wave delay. The pulse wave delay is defined as difference between the characteristic points i.e. the difference between the R wave in the electrocardiogram signal (ECG) and distinctive point in the photoplethysmogram (PPG) waveform. Obtaining values of the characteristic points (time stamps) are realized by correlation function...
In this paper, we model an essential feature of underwater mine hunting with the aim of suggesting improvements to existing search tactics. We derive the effect of correlation between multiple sonar images of an underwater mine target - where a correlator represents the relation between images of the same target. For example, with duplicate images of the same target the correlator shows the absence...
The motivating mission for the work presented in this paper is performing photo-surveys of areas of the deep ocean seafloor using an autonomous underwater vehicle (AUV). This paper describes a method for estimating the full terrain profile ahead of an AUV using an obstacle avoidance sonar. This allows the use of an existing trajectory planning method to optimize low altitude trajectories for high...
This paper presents a method for human action recognition from depth sequence. First, we subdivided the normalized motion energy vector into a set of segments, whose corresponding frame indices are used to partition a video. Then each sub-action is represented by three Depth Motion Maps (DMMs) to capture motion cues in three orthogonal projection views. Multi-scale Histogram of Oriented Gradients...
This paper aims to investigate the effect of distance metrics on the fitness landscape for model-based leakage localization and its impact on the performance of the differential evolution optimization algorithm applied to a theoretical water distribution network from literature.
This paper proposes an extended Constrained Local Model (CLM) formulation for aligning faces using depth information. The CLMs are popular methods that were initially designed to locate facial features in regular intensity images. Briefly, they combine a set of local detectors, one for each landmark, whose locations are regularized by a linear shape model. Fitting a CLM is usually framed as a two...
This paper proposes a novel Multiview Discriminative Analysis of Canonical Correlations (MDACC) for multiview learning. The proposed MDACC can capture discriminative features. Furthermore, we present a human action recognition framework by using MDACC to fuse multimodal features, which include the hierarchical Pyramid of Depth Motion Map (HP-DMM) for the depth images, the Histogram of Oriented Displacement...
The morphological similarity of anatomical structures is essential to the study of the species evolution. In this paper, we investigate the unsupervised shape similarity analysis by a random-forest-based metric. The dense continuous deformation fields are employed as the shape descriptors. The forest is built when given the unlabeled deformation fields, where the leaves can be seen as an optimal clustering...
This paper presents a simple and efficient method for action recognition based on the learning of an explicit representation for an intrinsic dynamic shape manifold of human action. The proposed model relies on a short temporal set of FastMap dimensionality reduction-based technique for embedding a sequence of raw moving silhouettes, associated to an action video into a low-dimensional space, in order...
In order to improve asset knowledge and avoid third part damages during road works, the localization of gas pipes in a non-destructive way has become a wide domain of research during these last years. Several devices have been developed in order to answer this problem. Acoustic, electromagnetic or RFID technologies are used to find pipes in the underground. Ground Penetrating Radar (GPR) is also used...
The automation and systemisation of the next generation of cognitive assessment approaches have the potential to change how clinicians assess and interact with patients. This may be especially pertinent in the case of delirium, as current methods often rely on the subjective opinion of clinicians and specialists, with potential for the condition to be overlooked or misdiagnosed. Currently, one of...
The exact measure of mitotic nuclei is a crucial parameter in breast cancer grading and prognosis. This can be achieved by improving the mitotic detection accuracy by careful design of segmentation and classification techniques. In this paper, segmentation of nuclei from breast histopathology images are carried out by Localized Active Contour Model (LACM) utilizing bio-inspired optimization techniques...
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