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This paper puts forward a new tracking algorithm based on Mean Shift algorithm and the Particle Filter algorithm. We combined the two algorithms efficiently based on the open structure system of both Mean Shift algorithm and the Particle Filter algorithm, and the model similar expression of establishment of the target, similarity measure and the selection of kernel function they have. The new algorithm...
In this work, we investigate the linear dynamic interactions between fluctuations in arterial CO2 that occur during normal breathing, and the BOLD fMRI signal. We cast this problem within a systems-theoretic framework, where we employ functional expansions for the estimation of the impulse responses in large regions of interest, as well as in individual voxels. We also implement classification schemes...
Corneal images acquired by in-vivo specular and confocal microscopy provide clinical information on the cornea endothelium health state. Indeed, the normal hexagonal shape of endothelial cells is usually affected by age and pathologies. At present, the analysis is based on manual or semi-automatic methods and the segmentation of a large number of endothelial cells is required for a meaningful estimation...
The motion dynamics and geometric information are considered to be one of the most useful features for infrared (IR) targets recognition. Especially for the exo-atmospheric target, when a target undergoes micro-motion dynamics in the outer space, such as mechanical vibrations or rotations, it would induce amplitude modulations on signature of target projected area along the Line-of-Sight (LOS) of...
If the pre-processing phase, in optical character recognition systems, is the heart of the recognition process, the segmentation stage is the "aorta" of this heart. This paper introduce a reliable segmentation technique for Arabic handwritten script. Number of techniques like, script height, character width, pen thickness and word/subword gaps are used to design an efficient segmentation...
To verify the validity of an tracking algorithm, its performance should be evaluated and compared with other algorithms. Unlike point target, the task of extended object tracking is to estimate the object shape in addition to its kinematic state. Especially for the shape estimation performance evaluation, there is a pressing need for measuring the degree of the similarity between the estimated shape...
This paper presents a novel online capable method for simultaneous estimation of human motion in terms of segment orientations and positions along with sensor-to-segment calibration parameters from inertial sensors attached to the body. In order to solve this ill-posed estimation problem, state-of-the-art motion, measurement and biomechanical models are combined with new stochastic equations and priors...
This paper presents a new approach based on extension deformation for extended object tracking (EOT). In this approach, the extension of an object is assumed to be deformed from a reference extension by moving some control points in the latter to those in the former. That is, the properties of an extension can be fully captured by the control points, given the reference extension. Thus, modeling and...
Tactile sensing for object shape estimation is a key ingredient for real world robots that need to do grasping and manipulation of unknown objects. Since the vision sensors are noisy and suffer from occlusions, the touch to sense approach is beneficial for complementary obtaining local but accurate shape information of objects. Executing exhaustive touches for an object is time consuming and unrealistic,...
The complex multivariate generalized Gaussian distribution (CMGGD) is a flexible parametrized distribution suitable for a variety of applications. Previous work in this area is either limited to the univariate case or, in the multivariate case, restricts the complex vectors, unjustifiably, to be circular. In both cases, algorithms for parameter estimation also suffer from convergence or accuracy limitations...
This study proposes the development of a simple remote-controlled daily assistive robot to assist physically challenged individuals. Specifically, we present a method for target object selection using a single click on a graphical user interface. Using this information, the robot can automatically estimate the unknown target object region to plan to grasp and fetch the object. The challenging task...
Photometric ambient occlusion estimation is to recover the local visibility of a scene from multiple illuminations at a fixed viewpoint. Its effectiveness is highly dependent on the amount of illuminations. In this paper, we study how to reliably extract photometric ambient occlusion from sparsely sampled illuminations. We specifically propose an effective relative entropy minimization framework to...
In this paper, we present a new framework for building change detection from monocular aerial imagery that automatically predicts building candidates based on adaptive local textural features with successive background removal. An adaptive local entropy feature is developed based on quadratic regression and Random Sample Consensus (RANSAC) for extracting potential building candidates. Then a majority...
Canopy vertical parameters, such as tree height, side shape and gap fraction are critical for forestry studies. However, it is not trivial to retrieve them from remotely sensed data. Currently, only LiDAR data can directly provide some of these parameters. Due to low availability and relatively high cost, it is still crucial to develop methodologies that can directly derive these parameters from other...
In this paper, a validity index method VDOGK, a variation of the index method VDO, for estimating the optimal number of clusters in datasets with concave-/elongated-shaped clusters is presented. The new index uses Gustafson-Kessel FCM to partition the dataset so that geometric-shape-sensitivity problem of FCM can be reduced. It is based on both dispersion and overlap measures, where the dispersion...
We present a new method for non-rigid registration with multiple features in this work. The proposed method is based on an alternating two-step process: correspondence estimation and transformation updating. We first define two vector features for measuring global and local structural differences between two point sets, respectively. We then combine the two features to build a multi-feature based...
This paper addresses the problem of fault estimation and fault-tolerant control for a class of non-Gaussian stochastic systems subject to simultaneous time-varying actuator and sensor faults. In this work, sensor faults, actuator faults, and general stochastic characteristics are taken into consideration in a unified framework. For such systems, the output distribution is adopted in designing the...
Mesh segmentation or shape decomposition is a crucial step in shape analysis, shape understanding, model retrieval, and shape composition, etc. To yield visually meaningful parts from an object, previous works suggest the concept of the minimal rule and the theory of part salience. However, they mostly rely on an integral of geodesic distance to approximate the part salience, which requires a high...
Depth estimation, which is mostly performed by stereo vision, is a remarkable task in vision and scene understanding. In this paper, depth map estimation from a single image is investigated and applied in pedestrian candidate generation. To recover accurate depth map from a single image, a Markov Random Field (MRF) model that incorporates both image depth cues and the relationships between different...
Nowadays surveys are common data source for empirical research in marketing, social sciences, and official statistic. Such studies often focus on correlation analysis. Survey questions typically have answer scales and collect ordered-categorical data. For this type of data a great way to measure association is to estimate polychoric correlation coefficient. It standardly assumes bivariate normal distribution...
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