No abstract

Most methods for the recognition of shape classes from 3D datasets focus on classifying clean, often manually generated models. However, 3D shapes obtained through acquisition techniques such as Structure-from-Motion or LIDAR scanning are noisy, clutter and holes. In that case global shape features-still dominating the 3D shape class recognition literature-are less appropriate. Inspired by 2D methods, recently researchers have started to work with local features. In keeping with this strand, we propose a new robust 3D shape classification method. It contains two main contributions. First, we extend a robust 2D feature descriptor, SURF, to be used in the context of 3D shapes. Second, we show how 3D shape class recognition can be improved by probabilistic Hough transform based methods, already popular in 2D.Through our experiments on partial shape retrieval, we show the power of the proposed 3D features. Their combination with the Hough transform yields superior results for class recognition on standard datasets. The potential for the applicability of such a method in classifying 3D obtained from Structure-from-Motion methods is promising, as we show in some initial experiments.

The effluent of a micro-scaled atmospheric pressure plasma jet (μ-APPJ) operated in helium with admixtures of water vapor (10 4 ppm) has been analyzed by means of cavity ring-down laser absorption spectroscopy and molecular beam mass spectrometry to measure hydroxyl (OH) radical densities, and by two-photon absorption laser-induced fluorescence spectroscopy to measure atomic oxygen (O) densities. Additionally, the performance of the bubbler as a source of water vapor in the helium feed gas has been carefully characterized and calibrated. The largest OH and O densities in the effluent of × − 2 10 cm 14 3 and × − 3.2 10 cm 13 3 , respectively, have been measured at around 6000 ppm. The highest selectivity is reached around 1500 ppm, where the OH density is at ∼63% of its maximum value and is 14 times larger than the O density. The measured density profiles and distance variations are compared to the results of a 2D axially symmetric fluid model of species transport and reaction kinetics in the plasma effluent. It is shown that the main loss of OH radicals in the effluent is their mutual reaction. In the case of O, reactions with other species than OH also have to be considered to explain the density decay in the effluent. The results presented here provide additional information for understanding the plasma-chemical processes in non-equilibrium atmospheric pressure plasmas. They also open the way to applying μ-APPJ with He/H 2 O as a selective source of OH radicals.

Abstract. The least trimmed squares estimator and the minimum covariance determinant estimator [6] are frequently used robust estimators of regression and of location and scatter. Consistency factors can be computed for both methods to make the estimators consistent at the normal model. However, for small data sets these factors do not make the estimator unbiased. Based on simulation studies we therefore construct formulas which allow us to compute small sample correction factors for all sample sizes and dimensions without having to carry out any new simulations. We give some examples to illustrate the e¤ect of the correction factor.

We consider robust principal component analysis based on multivariate MM-estimators. We first study the robustness and efficiency of these estimators, in particular regarding eigenvalues and eigenvectors. Then we focus on inference procedures based on a fast and robust bootstrap for MM-estimators. This method is an alternative to the approach based on the asymptotic distribution of the estimators, and can also be used to assess the stability of the principal components. A formal consistency proof for the bootstrap method is given and its finite-sample performance is investigated through simulations. We illustrate the use of the robust principal components method and the bootstrap inference on a real dataset.

Tooth autotransplantation (TAT) offers a viable biological approach to tooth replacement in children and adolescents. The aim of this study was to evaluate the outcome of the cone-beam computed tomographic (CBCT)-guided TAT compared to the conventional TAT protocol and to assess the 3-dimensional (3D) patterns of healing after CBCT-guided TAT (secondary aim). This study included 100 autotransplanted teeth in 88 patients. Each experimental group consisted of 50 transplants in 44 patients (31 males and 19 females). The mean (SD) age at the time of surgery was 10.7 (1.1) y for the CBCT-guided group. This was 10.6 (1.3) y for the conventional group. The mean (SD) follow-up period was 4.5 (3.1) y (range, 1.1 to 10.4 y). Overall survival rate for the CBCT-guided TAT was 92% with a success rate of 86% compared to an 84% survival rate and a 78% success rate for the conventional group (P > 0.005). The following measurements were extracted from the 3D analysis: root hard tissue volume (RV), root length (RL), apical foramen area (AFA), and mean and maximum dentin wall thickness (DWT). Overall, the mean (SD) percentage of tissue change was as follows: RV gain by 65.8% (34.6%), RL gain by 37.3% (31.5%), AFA reduction by 91.1% (14.9%), mean DWT increase by 107.9% (67.7%), and maximum DWT increase by 26.5% (40.1%). Principal component analysis (PCA) identified the mean DWT, RV, and maximum DWT as the parameters best describing the tissue change after TAT. Cluster analysis applied to the variables chosen by the PCA classified the CBCT group into 4 distinct clusters (C1 = 37.2%, C2 = 17.1%, C3 = 28.6%, C4 = 17.1%), revealing different patterns of tissue healing after TAT. The CBCT-guided approach increased the predictability of the treatment. The 3D analysis provided insights into the patterns of healing. CBCT-guided TAT could be adopted as an alternative for the conventional approach. (Clinical trial center and ethical board University Hospitals, KU Leuven: S55287; ClinicalTrials.gov Identifier: NCT02464202

The aims of this study were to determine the accuracy of a 3D computer model and stereolithographic (STL) replica when compared to the real tooth and to develop a cone beam computed tomography (CBCT)-based planning technique including surgical guide fabrication. A STL surgical guide and a tooth replica were fabricated using SimPlant Pro 12.1. To validate this process, tooth segmentation and replica design were prepared for comparison to an optical scan of the corresponding tooth. For surgical intervention, a dry dentate mandible was scanned using a Scanora CBCT and the donor tooth was segmented. The donor tooth was repositioned, and two guides were designed. These tooth replica and guides were used in socket preparation of the dry mandible. The 3D computer model of the segmented teeth and related STL models showed satisfactory results with an acceptable accuracy. The surfaces were within 0·25mm distance, but in some areas up to 2·5mm deviation were seen. The results showed that 79% of the points was between 0·25 and -0·25mm, 3% was overestimated (>0·25mm) and 18% was underestimated (<-0·25mm). The computer-based repositioning of the donor tooth and construction of tooth replica and guide allowed socket preparation before donor tooth extraction and optimization of the STL procedure for in vivo planning of CBCT-based autotransplantation.

Voltage shift and deformation in the hysteresis loop of Pb(Zr,Ti)O3 (PZT) capacitors have been studied by varying the annealing temperature after patterning the top sputter-deposited Pt electrode using reactive ion etch (RIE) with Ar gas. It was observed that the hysteresis loop of the film was seriously deformed by both sputtering and RIE induced defects. Voltage shift and polarization suppression can be explained by the charge trapping at electrode interfaces and at defect levels in the film, respectively. Space charges trapped at defect levels in the film suppress polarization parallel to poling direction, however, enhance polarization opposite to the poling direction.