965 resultados para morphology target tracking


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In order to improve the tracking and erosion performance of outdoor polymeric silicone rubber (SR) insulators used in HV power transmission lines, micron sized inorganic fillers are usually added to the base SR matrix. In addition, insulators used in high voltage dc transmission lines are designed to have increased creepage distance to mitigate the tracking and erosion problems. ASTM D2303 standard gives a procedure for finding the tracking and erosion resistance of outdoor polymeric insulator weathershed material samples under laboratory conditions for ac voltages. In this paper, inclined plane (IP) tracking and erosion tests similar to ASTM D2303 were conducted under both positive and negative dc voltages for silicone rubber samples filled with micron and nano sized particles to understand the phenomena occurring during such tests. Micron sized Alumina Trihydrate (ATH) and nano sized alumina fillers were added to silicone rubber matrix to improve the resistance to tracking and erosion. The leakage current during the tests and the eroded mass at the end of the tests were monitored. Scanning Electron Microscopy (SEM) and Energy dispersive Xray (EDX) studies were conducted to understand the filler dispersion and the changes in surface morphology in both nanocomposite and microcomposite samples. The results suggest that nanocomposites performed better than microcomposites even for a small filler loading (4%) for both positive and negative dc stresses. It was also seen that the tracking and erosion performance of silicone rubber is better under negative dc as compared to positive dc voltage. EDX studies showed migration of different ions onto the surface of the sample during the IP test under positive dc which has led to an inferior performance as compared to the performance under negative dc.

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The present work demonstrates a novel strategy to synthesize orthogonally bio-engineered magnetonanohybrids (MNPs) through the design of versatile, biocompatible linkers whose structure includes: (i) a robust anchor to bind with metal-oxide surfaces; (ii) tailored surface groups to act as spacers and (iii) a general method to implement orthogonal functionalizations of the substrate via ``click chemistry''. Ligands that possess the synthetic generality of features (i)-(iii) are categorized as ``universal ligands''. Herein, we report the synthesis of a novel, azido-terminated poly(ethylene glycol) (PEG) silane that can easily self-assemble on MNPs through hetero-condensation between surface hydroxyl groups and the silane end of the ligand, and simultaneously provide multiple clickable sites for high density, chemoselective bio-conjugation. To establish the universal-ligand-strategy, we clicked alkyl-functionalized folate onto the surface of PEGylated MNPs. By further integrating a near-infrared fluorescent (NIRF) marker (Alexa-Fluor 647) with MNPs, we demonstrated their folate-receptor mediated internalization inside cancer cells and subsequent translocation into lysosomes and mitochondria. Ex vivo NIRF imaging established that the azido-PEG-silane developed in course of the study can effectively reduce the sequestration of MNPs by macrophage organs (viz. liver and spleen). These folate-PEG-MNPs were not only stealth and noncytotoxic but their dual optical and magnetic properties aided in tracking their whereabouts through combined magnetic resonance and optical imaging. Together, these results provided a strong motivation for the future use of the ``universal ligand'' strategy towards development of ``smart'' nanohybrids for theragnostic applications.

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Real-time object tracking is a critical task in many computer vision applications. Achieving rapid and robust tracking while handling changes in object pose and size, varying illumination and partial occlusion, is a challenging task given the limited amount of computational resources. In this paper we propose a real-time object tracker in l(1) framework addressing these issues. In the proposed approach, dictionaries containing templates of overlapping object fragments are created. The candidate fragments are sparsely represented in the dictionary fragment space by solving the l(1) regularized least squares problem. The non zero coefficients indicate the relative motion between the target and candidate fragments along with a fidelity measure. The final object motion is obtained by fusing the reliable motion information. The dictionary is updated based on the object likelihood map. The proposed tracking algorithm is tested on various challenging videos and found to outperform earlier approach.

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We propose a novel space-time descriptor for region-based tracking which is very concise and efficient. The regions represented by covariance matrices within a temporal fragment, are used to estimate this space-time descriptor which we call the Eigenprofiles(EP). EP so obtained is used in estimating the Covariance Matrix of features over spatio-temporal fragments. The Second Order Statistics of spatio-temporal fragments form our target model which can be adapted for variations across the video. The model being concise also allows the use of multiple spatially overlapping fragments to represent the target. We demonstrate good tracking results on very challenging datasets, shot under insufficient illumination conditions.

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We have synthesized Ag-Cu alloy nanoparticles of four different compositions by using the laser ablation technique with the target under aqueous medium. Following this, we report a morphological transition in the nanoparticles from a normal two-phase microstructure to a structure with random segregation and finally a core shell structure at small sizes as a function of Cu concentration. To illustrate the composition dependence of morphology, we report observations carried out on nanoparticles of two different sizes: similar to 5 and similar to 20 nm. The results could be rationalized through the thermodynamic modeling of free energy of phase mixing and wettability of the alloying phases.

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Visual tracking is an important task in various computer vision applications including visual surveillance, human computer interaction, event detection, video indexing and retrieval. Recent state of the art sparse representation (SR) based trackers show better robustness than many of the other existing trackers. One of the issues with these SR trackers is low execution speed. The particle filter framework is one of the major aspects responsible for slow execution, and is common to most of the existing SR trackers. In this paper,(1) we propose a robust interest point based tracker in l(1) minimization framework that runs at real-time with performance comparable to the state of the art trackers. In the proposed tracker, the target dictionary is obtained from the patches around target interest points. Next, the interest points from the candidate window of the current frame are obtained. The correspondence between target and candidate points is obtained via solving the proposed l(1) minimization problem. In order to prune the noisy matches, a robust matching criterion is proposed, where only the reliable candidate points that mutually match with target and candidate dictionary elements are considered for tracking. The object is localized by measuring the displacement of these interest points. The reliable candidate patches are used for updating the target dictionary. The performance and accuracy of the proposed tracker is benchmarked with several complex video sequences. The tracker is found to be considerably fast as compared to the reported state of the art trackers. The proposed tracker is further evaluated for various local patch sizes, number of interest points and regularization parameters. The performance of the tracker for various challenges including illumination change, occlusion, and background clutter has been quantified with a benchmark dataset containing 50 videos. (C) 2014 Elsevier B.V. All rights reserved.

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Displacement estimation is a key step in the evaluation of tissue elasticity by quasistatic strain imaging. An efficient approach may incorporate a tracking strategy whereby each estimate is initially obtained from its neighbours' displacements and then refined through a localized search. This increases the accuracy and reduces the computational expense compared with exhaustive search. However, simple tracking strategies fail when the target displacement map exhibits complex structure. For example, there may be discontinuities and regions of indeterminate displacement caused by decorrelation between the pre- and post-deformation radio frequency (RF) echo signals. This paper introduces a novel displacement tracking algorithm, with a search strategy guided by a data quality indicator. Comparisons with existing methods show that the proposed algorithm is more robust when the displacement distribution is challenging.

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NiOx thin films were deposited by reactive DC-magnetron sputtering from a nickel metal target in Ar + O-2 with the relative O-2 content of 5%. Thermal annealing effects on optical properties and surface morphology of NiOx, films were investigated by X-ray photoelectron spectroscopy, thermogravimetric analysis, scanning electron microscope and optical measurement. The results showed that the changes in optical properties and surface morphology depended on the temperature. The surface morphology of the films changed obviously as the annealing temperature increased due to the reaction NiOx -> NiO + O-2 releasing O-2. The surface morphology change was responsible for the variation of the optical properties of the films. The optical contrast between the as-deposited films and 400 degrees C annealed films was about 52%. In addition, the relationship of the optical energy band gap with the variation of annealing temperature was studied. (c) 2006 Elsevier B.V. All rights reserved.

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In this paper, we describe a video tracking application using the dual-tree polar matching algorithm. The models are specified in a probabilistic setting, and a particle ilter is used to perform the sequential inference. Computer simulations demonstrate the ability of the algorithm to track a simulated video moving target in an urban environment with complete and partial occlusions. © The Institution of Engineering and Technology.

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Algorithms are presented for detection and tracking of multiple clusters of co-ordinated targets. Based on a Markov chain Monte Carlo sampling mechanization, the new algorithms maintain a discrete approximation of the filtering density of the clusters' state. The filters' tracking efficiency is enhanced by incorporating various sampling improvement strategies into the basic Metropolis-Hastings scheme. Thus, an evolutionary stage consisting of two primary steps is introduced: 1) producing a population of different chain realizations, and 2) exchanging genetic material between samples in this population. The performance of the resulting evolutionary filtering algorithms is demonstrated in two different settings. In the first, both group and target properties are estimated whereas in the second, which consists of a very large number of targets, only the clustering structure is maintained. © 2009 IFAC.

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BACKGROUND: Despite the widespread use of sensors in engineering systems like robots and automation systems, the common paradigm is to have fixed sensor morphology tailored to fulfill a specific application. On the other hand, robotic systems are expected to operate in ever more uncertain environments. In order to cope with the challenge, it is worthy of note that biological systems show the importance of suitable sensor morphology and active sensing capability to handle different kinds of sensing tasks with particular requirements. METHODOLOGY: This paper presents a robotics active sensing system which is able to adjust its sensor morphology in situ in order to sense different physical quantities with desirable sensing characteristics. The approach taken is to use thermoplastic adhesive material, i.e. Hot Melt Adhesive (HMA). It will be shown that the thermoplastic and thermoadhesive nature of HMA enables the system to repeatedly fabricate, attach and detach mechanical structures with a variety of shape and size to the robot end effector for sensing purposes. Via active sensing capability, the robotic system utilizes the structure to physically probe an unknown target object with suitable motion and transduce the arising physical stimuli into information usable by a camera as its only built-in sensor. CONCLUSIONS/SIGNIFICANCE: The efficacy of the proposed system is verified based on two results. Firstly, it is confirmed that suitable sensor morphology and active sensing capability enables the system to sense different physical quantities, i.e. softness and temperature, with desirable sensing characteristics. Secondly, given tasks of discriminating two visually indistinguishable objects with respect to softness and temperature, it is confirmed that the proposed robotic system is able to autonomously accomplish them. The way the results motivate new research directions which focus on in situ adjustment of sensor morphology will also be discussed.

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This paper studies the development of a real-time stereovision system to track multiple infrared markers attached to a surgical instrument. Multiple stages of pipeline in field-programmable gate array (FPGA) are developed to recognize the targets in both left and right image planes and to give each target a unique label. The pipeline architecture includes a smoothing filter, an adaptive threshold module, a connected component labeling operation, and a centroid extraction process. A parallel distortion correction method is proposed and implemented in a dual-core DSP. A suitable kinematic model is established for the moving targets, and a novel set of parallel and interactive computation mechanisms is proposed to position and track the targets, which are carried out by a cross-computation method in a dual-core DSP. The proposed tracking system can track the 3-D coordinate, velocity, and acceleration of four infrared markers with a delay of 9.18 ms. Furthermore, it is capable of tracking a maximum of 110 infrared markers without frame dropping at a frame rate of 60 f/s. The accuracy of the proposed system can reach the scale of 0.37 mm RMS along the x- and y-directions and 0.45 mm RMS along the depth direction (the depth is from 0.8 to 0.45 m). The performance of the proposed system can meet the requirements of applications such as surgical navigation, which needs high real time and accuracy capability.

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This paper studies the development of a real-time stereovision system to track multiple infrared markers attached to a surgical instrument. Multiple stages of pipeline in field-programmable gate array (FPGA) are developed to recognize the targets in both left and right image planes and to give each target a unique label. The pipeline architecture includes a smoothing filter, an adaptive threshold module, a connected component labeling operation, and a centroid extraction process. A parallel distortion correction method is proposed and implemented in a dual-core DSP. A suitable kinematic model is established for the moving targets, and a novel set of parallel and interactive computation mechanisms is proposed to position and track the targets, which are carried out by a cross-computation method in a dual-core DSP. The proposed tracking system can track the 3-D coordinate, velocity, and acceleration of four infrared markers with a delay of 9.18 ms. Furthermore, it is capable of tracking a maximum of 110 infrared markers without frame dropping at a frame rate of 60 f/s. The accuracy of the proposed system can reach the scale of 0.37 mm RMS along the x- and y-directions and 0.45 mm RMS along the depth direction (the depth is from 0.8 to 0.45 m). The performance of the proposed system can meet the requirements of applications such as surgical navigation, which needs high real time and accuracy capability.

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An improved technique for 3D head tracking under varying illumination conditions is proposed. The head is modeled as a texture mapped cylinder. Tracking is formulated as an image registration problem in the cylinder's texture map image. To solve the registration problem in the presence of lighting variation and head motion, the residual error of registration is modeled as a linear combination of texture warping templates and orthogonal illumination templates. Fast and stable on-line tracking is then achieved via regularized, weighted least squares minimization of the registration error. The regularization term tends to limit potential ambiguities that arise in the warping and illumination templates. It enables stable tracking over extended sequences. Tracking does not require a precise initial fit of the model; the system is initialized automatically using a simple 2-D face detector. The only assumption is that the target is facing the camera in the first frame of the sequence. The warping templates are computed at the first frame of the sequence. Illumination templates are precomputed off-line over a training set of face images collected under varying lighting conditions. Experiments in tracking are reported.

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An improved technique for 3D head tracking under varying illumination conditions is proposed. The head is modeled as a texture mapped cylinder. Tracking is formulated as an image registration problem in the cylinder's texture map image. The resulting dynamic texture map provides a stabilized view of the face that can be used as input to many existing 2D techniques for face recognition, facial expressions analysis, lip reading, and eye tracking. To solve the registration problem in the presence of lighting variation and head motion, the residual error of registration is modeled as a linear combination of texture warping templates and orthogonal illumination templates. Fast and stable on-line tracking is achieved via regularized, weighted least squares minimization of the registration error. The regularization term tends to limit potential ambiguities that arise in the warping and illumination templates. It enables stable tracking over extended sequences. Tracking does not require a precise initial fit of the model; the system is initialized automatically using a simple 2D face detector. The only assumption is that the target is facing the camera in the first frame of the sequence. The formulation is tailored to take advantage of texture mapping hardware available in many workstations, PC's, and game consoles. The non-optimized implementation runs at about 15 frames per second on a SGI O2 graphic workstation. Extensive experiments evaluating the effectiveness of the formulation are reported. The sensitivity of the technique to illumination, regularization parameters, errors in the initial positioning and internal camera parameters are analyzed. Examples and applications of tracking are reported.