Multi-view Technique Research Articles

Multiview Clustering via Hypergraph Induced Semi-Supervised Symmetric Nonnegative Matrix Factorization

Nonnegative matrix factorization (NMF) based multiview technique has been commonly used in multiview data clustering tasks. However, previous NMF based multiview clustering approaches fail to take advantage of a small amount of supervisory information to effectively improve the clustering performance, and are easily affected by the additional post-processing method in clustering tasks. To cope with these issues, a novel framework named multiview clustering via hypergraph induced semi-supervised symmetric NMF (MVCHSS) is proposed in this paper for multiview data clustering applications. Specifically, the proposed method has the following features: 1) a new multiview based hypergraph pairwise constraints propagation (MHPCP) algorithm is developed in MVCHSS to construct a set of informative similarity matrices, revealing the high-order relationships effectively and fully utilizing the limited pairwise constraint supervisory information among samples of each view data; 2) the obtained similarity matrices with much supervisory information are not only enforced into the symmetric NMF (SNMF) model, but also incorporated into the graph regularization for each view data; 3) the optimization problem of MVCHSS is formulated for multiview data clustering tasks to acquire a more discriminative clustering indicator matrix (or called consensus assignment matrix) without additional post-processing method. Moreover, the proof of convergence and the computational complexity for MVCHSS are presented. Extensive experiments on five multiview datasets demonstrate that the proposed MVCHSS framework outperforms several state-of-the-art multiview clustering methods.

A deep learning pipeline for the automated segmentation of posterior limb of internal capsule in preterm neonates

Segmentation of specific brain tissue from MRI volumes is of great significance for brain disease diagnosis, progression assessment, and monitoring of neurological conditions. Manual segmentation is time-consuming, laborious, and subjective, which significantly amplifies the need for automated processes. Over the last decades, the active development in the field of deep learning, especially convolutional neural networks (CNNs), and the associated performance improvements have increased the demand for the application of CNN-based methods to provide consistent measurements and quantitative analyses. In this paper, we present an efficient deep learning approach for the segmentation of brain tissue. More specifically, we address the problem of segmentation of the posterior limb of the internal capsule (PLIC) in preterm neonates. To this end, we propose a CNN-based pipeline comprised of slice-selection modules and a multi-view segmentation model, which exploits the 3D information contained in the MRI volumes to improve segmentation performance. One special feature of the proposed method is its ability to identify one desired slice out of the whole image volume, which is relevant for pediatricians in terms of prognosis. To increase computational efficiency, we apply a strategy that automatically reduces the information contained in the MRI volumes to its relevant parts. Finally, we conduct an expert rating alongside standard evaluation metrics, such as dice score, to evaluate the performance of the proposed framework. We demonstrate the benefit of the multi-view technique by comparing it with its single-view counterparts, which reveals that the proposed method strikes a good balance between exploiting the available image information and reducing the required computing power compared to 3D segmentation networks. Standard evaluation metrics as, well as expert-based assessment, confirm the good performance of the proposed framework, with the latter being more relevant in terms of clinical applicability. We demonstrate that the proposed deep learning pipeline can compete with the experts in terms of accuracy. To prove the generalisability of the proposed method, we additionally assess our deep learning pipeline to data from the Developing Human Connectome Project (dHCP).

Patient expenditure prediction using deep learning framework

Measurement of patient expenditure in healthcare is a critical task that has a variety of applications, including provider profiling, accountable care management, and capitated medical payment adjustment. Currently available methods rely on manually built features and linear regression-based models, both of which need a significant amount of medical domain expertise. and have low prediction accuracy. This study develops a multi-view deep learning system for forecasting future healthcare costs at the individual level based on prior claims data. Our multi-view technique efficiently models heterogeneous data such patient demographics, medical codes, medication usages, and facility usage. To execute spending forecasting tasks, we employed a real-world paediatric dataset with approximately 450,000 patients. According to the empirical data, our proposed technique beats all baselines for predicting medical cost. In the sphere of healthcare, these insights help to improve preventative and responsible care.

Inverse Multiview. I. Multicalibrator Inverse Phase Referencing for Microarcsecond Very Long Baseline Interferometry Astrometry

Very Long Baseline Interferometry (VLBI) astrometry is a well established technique for achieving ±10 μas parallax accuracies at frequencies well above 10 GHz. At lower frequencies, uncompensated interferometer delays associated with the ionosphere play the dominant role in limiting the astrometric accuracy. Multiview is a novel VLBI calibration method, which uses observations of multiple quasars to accurately model and remove time-variable, directional-dependent changes to the interferometer delay. Here we extend the Multiview technique by phase-referencing data to the target source (“inverse Multiview”) and test its performance. Multiple observations with a four-antenna VLBI array operating at 8.3 GHz show single-epoch astrometric accuracies near 20 μas for target–reference quasar separations up to about 7°. This represents an improvement in astrometric accuracy by up to an order of magnitude compared to standard phase-referencing.

Development of a multi-view and geo-event-driven real-time collaborative GIS

ABSTRACT Supporting distributed real-time collaborative work has become an important development trend in GIS. It enables group users to cooperate and improve the use of scientific data and collaboration technologies. Real-time collaborative GIS (RCGIS) provides a platform for supporting synchronous collaboration using geospatial data in various forms. Traditional RCGIS generally works on a single map view, which has the disadvantage of collaborative interface confusion. The traditional system-driven mechanism of RCGIS is a computer-interaction event that has the disadvantage of an unfriendly collaborative perception. This paper presents a design and prototype of a RCGIS based on multi-view and geo-event driven mechanisms. The geo-event-driven mechanism provides users with a smoother collaborative perception and interactions that are more natural and friendly. The collaboration process for a GIS that is driven by geo-events is also discussed. A multi-view technique is used to make real-time GIS collaboration more orderly. The paper also proposes a synchronization strategy for public–private views. Finally, walk-through examples are used to demonstrate the use of RCGIS within a web environment.

Approximated super multi-view head-mounted display to reduce visual fatigue.

To reduce the visual fatigue of the head-mounted displays, we propose an approximated super multi-view technique in which multiple viewpoints are generated two-dimensionally with an interval smaller than the pupil diameter using the time multiplexing technique, and left and right virtual images are two-dimensionally shifted in synchronization with the viewpoint generation. The proposed technique enlarges the depth of field of eyes to provide the accommodation-invariant feature so that the vergence-accommodation conflict is mitigated. We constructed an experimental system by using two LED arrays for the viewpoint generation and one LCD panel vibrated by two stepping motors. The proposed technique was then experimentally validated.

Performance evaluation of underwater image pre-processing algorithms for the improvement of multi-view 3D reconstruction

<p class="Abstract">3D models of submerged structures and underwater archaeological finds are widely used in various and different applications, such as monitoring, analysis, dissemination, and inspection. Underwater environments are characterised by poor visibility conditions and the presence of marine flora and fauna. Consequently, the adoption of passive optical techniques for the 3D reconstruction of underwater scenarios is a highly challenging task.</p>This article presents a performance analysis conducted on a multi-view technique that is commonly used in air in order to highlight its limits in the underwater environment and then provide guidelines for the accurate modelling of a submerged site in poor visibility conditions. A performance analysis has been performed by comparing different image enhancement algorithms, and the results have been adopted to reconstruct an area of 40 m<sup>2</sup> at a depth of about 5 m at the underwater archaeological site of Baiae (Italy).

Super multi-view near-eye display to solve vergence–accommodation conflict

A super multi-view (SMV) technique is applied to near-eye displays to solve the vergence-accommodation conflict that causes visual fatigue. The proposed SMV near-eye display employs a high-speed spatial light modulator (SLM), a two-dimensional (2D) light source array, and an imaging optics for each eye. The imaging optics produces a virtual image of the SLM and real images of the light sources to generate a 2D array of viewpoints. The SMV images are generated using a time-multiplexing technique: the multiple light sources sequentially emit light while the SLM synchronously displays corresponding parallax images. A monocular experimental system was constructed using a ferroelectric liquid crystal display and an LED array. A full-parallax SMV image generation with 21 viewpoints was demonstrated and a comparison of full-parallax and horizontal parallax SMV images provided.

MultiView High Precision VLBI Astrometry at Low Frequencies

AbstractObservations at low frequencies (<8GHz) are dominated by distinct direction dependent ionospheric propagation errors, which place a very tight limit on the angular separation of a suitable phase referencing calibrator and astrometry. To increase the capability for high precision astrometric measurements an effective calibration strategy of the systematic ionospheric propagation effects that is widely applicable is required. The MultiView technique holds the key to the compensation of atmospheric spatial-structure errors, by using observations of multiple calibrators and two dimensional interpolation. In this paper we present the first demonstration of the power of MultiView using three calibrators, several degrees from the target, along with a comparative study of the astrometric accuracy between MultiView and phase-referencing techniques. MultiView calibration provides an order of magnitude improvement in astrometry with respect to conventional phase referencing, achieving ~100micro-arcseconds astrometry errors in a single epoch of observations, effectively reaching the thermal noise limit.

MultiView High Precision VLBI Astrometry at Low Frequencies

Abstract The arrival of the Square Kilometer Array (SKA) will revitalize all aspects of Very Long Baseline Interferometry (VLBI) astronomy at lower frequencies. In the last decade, there have been huge strides toward routinely achieving high precision VLBI astrometry at frequencies dominated by tropospheric contributions, most notably at 22 GHz, using advanced phase-referencing techniques. Nevertheless, to increase the capability for high precision astrometric measurements at low radio frequencies (<8 GHz), an effective calibration strategy of the systematic ionospheric propagation effects that is widely applicable is required. Observations at low frequencies are dominated by distinct direction-dependent ionospheric propagation errors, which place a very tight limit on the angular separation of a suitable phase-referencing calibrator. The MultiView technique holds the key to compensating for atmospheric spatial-structure errors, by using observations of multiple calibrators and two-dimensional interpolation in the visibility domain. In this paper we present the first demonstration of the power of MultiView using three calibrators, several degrees from the target, along with a comparative study of the astrometric accuracy between MultiView and phase-referencing techniques. MultiView calibration provides an order of magnitude improvement in astrometry with respect to conventional phase referencing, achieving ∼100 μas astrometry errors in a single epoch of observations, effectively reaching the thermal noise limit. MultiView will achieve its full potential with the enhanced sensitivity and multibeam capabilities of SKA and the pathfinders, which will enable simultaneous observations of the target and calibrators. Our demonstration indicates that the 10 μas goal of astrometry at ∼1.6 GHz using VLBI with SKA is feasible using the MultiView technique.

Evaluation of X-ray visualization techniques for vertical depth judgments in underground exploration

This paper investigates depth judgment-related performances of X-ray visualization techniques for rendering fully occluded geometries in augmented reality. The techniques we selected for this evaluation are careless overlay (CO), edge overlay (EO), excavation box (EB) and a cross-sectional visualization technique (CS). We have designed and conducted a comprehensive user study with 16 participants to examine and analyze the effects related to visualization techniques, having additional virtual objects and the scale of the vertical depths. To the best of our knowledge, this is the first user study on judged vertical depth distances that these techniques were compared against each other. We report our findings using four dependent variables: accuracy, signed error, absolute error and response time to shed some light into real-world performances and also to reveal estimation tendencies of each technique. Our findings suggest similar and better performance for EB, CS compared to CO and EO. We also observed significantly better results for EB and CS techniques when judging Top and Bottom distances compared to Middle distances. Derived from our findings, we proposed a new visualization technique for underground investigation with multiple views. The multi-view technique is our own implementation inspired by magic lens and cross-sectional visualizations with correlating displays.

Multi-modal and multi-layout discriminative learning for placental maturity staging

Placental maturity staging is a challenging task due to complex imaging procedure, fetal and gestational age variations. To address this issue, we extract features not only from B-mode gray-scale ultrasound (US) images, but also from color Doppler energy (CDE) images. Based on these features, we propose a method to automatically determine the placental maturity by harnessing multi-view and multi-layout discriminative learning fusion. Specifically, we devise a multi-view technique to generate features of complementary information. Scale invariant features are extracted from image locally, and a Gaussian mixture model (GMM) is then applied to summarize the high-level information features. The clustering representatives from GMM are encoded via a multi-layout Fisher vector (MFV) instead of traditional Fisher vector (FV) to aggregate features based on their spatial information. We apply a multi-layout feature encoding method to improve the staging performance using discriminative learning technique. Extensive experimental results demonstrate that our method achieves promising performance in placental maturity staging and outperforms existing methods.

Biomedical Applications of Stereoscopy for Three-Dimensional Surface Reconstruction in Scanning Electron Microscopes

The scanning electron microscope (SEM) offers two-dimensional (2D) micrographs of three-dimensional (3D) objects due to its inherent operating mechanisms. To overcome this limitation, other devices have been used for quantitative morphological analysis. Many efforts have been made on the applications of software-based approaches to 3D reconstruction and measurements by SEM. Based on the acquisition of two stereo images, a multi-view technique consists of two parts: (i) geometric calibration and (ii) image matching. Quantitative morphological parameters such as height and depth could be nondestructively measured by SEM combined with special software programs. It is also possible to obtain conventional surface parameters such as roughness and volume of biomedical specimens through 3D SEM surface reconstruction. There is growing evidence that conventional 2D SEM without special electron detectors can be transformed to 3D SEM for quantitative measurements in biomedical research.

Novel optical method for high precision measurements of dental structures

Realising a fine dental impression is an essential task to obtain a correct diagnostic cast. Non-contact optical methods achieve high precision measurements and maximise patient’s comfort. This paper aims to implement an advanced multiview optical technique for reconstructing three-dimensional dental elements. The main novelty of the proposed approach is to integrate fringe projection and image correlation techniques, thus increasing accuracy of dental reconstruction. This study represents a step towards the standardisation of a non-contact protocol for dental measurements.

Young Investigator Award session - Basic Science * Intracardiac flows and pressures

Young Investigator Award session - Basic Science * Intracardiac flows and pressures

Event-driven graphical representative schema for job-shop-type material flows and data computing usingautomatic identification of radio frequency identification tags

In order to track material flow in job shops more accurately and effectively, this paper presents an ‘event-triggering time-state’ graphical schema-based operation model for describing and formalizing material flow. At the same time, the operation model is associated with valid radio frequency identification (RFID) tags. Then judgement rules are proposed for identifying and picking out valid ones from all found RFID tags. In this way, material flow can be tracked effectively and in real time through use of the multi-view technique. Finally, a case is studied for demonstrating the feasibility and availability of the proposed model and method.

Simultaneous Registration of Multiple Corresponding Point Sets

We present a new technique for the simultaneous registration of multiple corresponding point sets with rigid 3D transformations. This class of problems is a generalization of the classic pairwise point set registration task, involving multiple views with multiple correspondences existing between them. The proposed technique requires the computation of a constant matrix which encodes the point correspondence information, followed by an efficient iterative algorithm to compute the optimal rotations. The optimal translations are then recovered directly through the solution of a linear equation system. The algorithm supports weighting of data according to confidence, and we show how it may be incorporated into two robust estimation frameworks to detect and reject outlier data. We have integrated our method into a generalized multiview ICP surface matching system and tested it with synthetic and real data. These tests indicate that the technique is accurate and efficient. The algorithm also compares favorably to another multiview technique from the literature.

Giambologna, Narrator of the Catholic Reformation by Mary Weitzel Gibbons

724book reviews were a feature of the EngUsh history of those days. Persons the man and the priest gets lost in the clutter. His important work Ui manning and helping finance the seminaries comes out clearly, but his work as a writer—and he was one of the best EngUsh stylists of his day—is slighted. One would have preferred to see a clearer picture of Persons' character and personaUty. There do exist some published efforts along this line, especiaUy those focusing in on the last dozen years of his life, which he spent mostly as rector of the EngUsh CoUege, Rome. The reader rarely gets a hint 'why Persons inspires so much devotion on the one hand and so much enmity on the other. He enjoyed the complete confidence of Claudio Aquaviva, one of the greatest Jesuit generals. PhUip II of Spain trusted and revered him. He was a close collaborator of WiUiam Cardinal Allen and was highly regarded by his Jesuit brethren on the English mission. Nevertheless, there is every indication that almost aU Protestants and a good number of EngUsh Catholics opposed his policies and revUed his person. Nevertheless, this biography is a good first step. Edwards has addressed the most difficult and puzzling side ofhis subject. It wUl be easier for future biographers to fiU Ui the blanks, especiaUy if they have access to a good edition of aU of Persons' letters. This is a book that students ofJesuit history, English history, and the Reformation wUl have to read. I would recommend that they do so surrounded by reference books. It wUl repay thetf effort. Thomas H. Clancy, SJ. JesuitArchives, New Orleans Giambologna, Narrator of the Catholic Reformation. By Mary Weitzel Gibbons . [California Studies in the History of Art, XXXIIL] (Berkeley: University of California Press. 1995. Pp. xviii, 262; 13 colorplates, 81 black and white figures. $50.00.) Mary Gibbons successfully challenges the generaUy held view that Giambologna was not interested in subject matter. She demonstrates that the style he invented for the bronze reUefs of Christ's Passion in the Grimani Chapel in Genoa was his response to the newly voiced requirements of the CathoUc Reformation that art be legible and comprehensible to the worshiper. She thus removes these works from the context oflate maniera court art and places them firmly in the avant-garde of Baroque reUgious art. The chapel, commissioned Ui 1579 by Luca Grimani, a prominent Genoese who would later serve as doge, has been neglected because it was destroyed when the church of San Francesco di Castelletto was suppressed under BOOK REVIEWS725 Napoleon and Giambologna's bronzes transferred to the university. The author reconstructs the Grimani sepulcral chapel with the aid of the artist's contemporary Salviati Chapel Ln San Marco Ui Florence, which she caU his "most important extant architectural and sculptural complex" (p. 27), and other precedents where painting and sculpture were combined. She associates die rare pairing of a series ofVirtues with a Passion cycle to the CatiioUc Reformation's focus on good works and the new catechism of 1566 that joined these two elements (p. 57). Passion cycles took on new prominence with the post-Tridentine emphasis on the Eucharist as first among the sacraments, insistence upon the real presence Ui the consecrated host, and the desirabUity offrequent communion for the faithful. The Passion story reminded the worshiper that Christ's sacrifice was made for humankind's redemption, as celebrated m the Eucharist. The prominence ofPUate in Giambologna's cycle is linked to the dUemma of choosing between poUtical expediency and personal conscience, faced by the patron Grimani as a prominent member of the Genoese government. The final chapter, "Giambologna's Narrative Method," contains the essential argument. The artist's technique in the bronze reliefs is shown to be an adaptation of the multiview technique for which he is famous in his statues Ui the round, like the Rape ofthe Sabines. By means of a series of photographs of the reUefs shot from three angles, subtle variations In the narrative are revealed. The spectator's eye is kept Ui constant motion, rendering the narrative dynamic and serving to involve the worshiper. Giambologna's reUefs are contrasted witii...

A high-quality 3D multiview model-building technique based on CAD

In this paper, we propose a method for building a high-quality 3D model efficiently from a CAD model. We automatically build the high-quality 3D model of an object by accurately extracting the 3D multiview features from the CAD model with the object-precision method instead of the existing image-precision method. Precision of the features from the image-precision method is limited to the precision of the image resolution and varies with the view distance and view-up vector. Since we exploit the object-precision method to extract the 3D multiview features, the precision of the features is equal to the precision at which the object is defined in the CAD and is independent of the view distance and view-up vector.

Multiview technique for SEM study of intestinal villi

Multiview technique for SEM study of intestinal villi