Algorithms For Automatic And Robust Registration Of 3D Head Scans

wo methods for registering laser-scans of human heads and transforming them to a new semantically consistent topology defined by a user-provided template mesh are described. Both algorithms are stated within the Iterative Closest Point framework. The first method is based on finding landmark correspondences by iteratively registering the vicinity of a landmark with a re-weighted error function. Thin-plate spline interpolation is then used to deform the template mesh and finally the scan is resampled in the topology of the deformed template. The second algorithm employs a morphable shape model, which can be computed from a database of laser-scans using the first algorithm. It directly optimizes pose and shape of the morphable model. The use of the algorithm with PCA mixture models, where the shape is split up into regions each described by an individual subspace, is addressed. Mixture models require either blending or regularization strategies, both of which are described in detail. For both algorithms, strategies for filling in missing geometry for incomplete laser-scans are described. While an interpolation-based approach can be used to fill in small or smooth regions, the model-driven algorithm is capable of fitting a plausible complete head mesh to arbitrarily small geometry, which is known as "shape completion". The importance of regularization in the case of extreme shape completion is shown.

Assessment of a robust opportunistic routing for video transmission in dynamic topologies

Mobile multimedia ad hoc services run on dynamic topologies due to node mobility or failures and wireless channel impairments. A robust routing service must adapt to topology changes with the aim of recovering or maintaining the video quality level and reducing the impact of the user's experience. In those scenarios, beacon-less Opportunistic Routing (OR) increases the robustness by supporting routing decisions in a completely distributed manner based on protocol-specific characteristics. However, the existing beacon-less OR approaches do not efficiently combine multiple metrics for forwarding selection, which cause higher packet loss rate, and consequently reduce the video quality level. In this paper, we assess the robustness and reliability of our recently developed OR protocol under node failures, called cross-layer Link quality and Geographical-aware OR protocol (LinGO). Simulation results show that LinGO achieves multimedia dissemination with QoE support and robustness in scenarios with dynamic topologies.

Robust Denoising using Feature and Color Information

We propose a method that robustly combines color and feature buffers to denoise Monte Carlo renderings. On one hand, feature buffers, such as per pixel normals, textures, or depth, are effective in determining denoising filters because features are highly correlated with rendered images. Filters based solely on features, however, are prone to blurring image details that are not well represented by the features. On the other hand, color buffers represent all details, but they may be less effective to determine filters because they are contaminated by the noise that is supposed to be removed. We propose to obtain filters using a combination of color and feature buffers in an NL-means and cross-bilateral filtering framework. We determine a robust weighting of colors and features using a SURE-based error estimate. We show significant improvements in subjective and quantitative errors compared to the previous state-of-the-art. We also demonstrate adaptive sampling and space-time filtering for animations.

Robust Proximal Femur Segmentation in Conventional X-Ray Images via Random Forest Regression on Multi-resolution Gradient Features

In this paper, we propose a fully automatic, robust approach for segmenting proximal femur in conventional X-ray images. Our method is based on hierarchical landmark detection by random forest regression, where the detection results of 22 global landmarks are used to do the spatial normalization, and the detection results of the 59 local landmarks serve as the image cue for instantiation of a statistical shape model of the proximal femur. To detect landmarks in both levels, we use multi-resolution HoG (Histogram of Oriented Gradients) as features which can achieve better accuracy and robustness. The efficacy of the present method is demonstrated by experiments conducted on 150 clinical x-ray images. It was found that the present method could achieve an average point-to-curve error of 2.0 mm and that the present method was robust to low image contrast, noise and occlusions caused by implants.

A Closed-Form, Consistent and Robust Solution to Uncalibrated Photometric Stereo Via Local Diffuse Reflectance Maxima

Images of an object under different illumination are known to provide strong cues about the object surface. A mathematical formalization of how to recover the normal map of such a surface leads to the so-called uncalibrated photometric stereo problem. In the simplest instance, this problem can be reduced to the task of identifying only three parameters: the so-called generalized bas-relief (GBR) ambiguity. The challenge is to find additional general assumptions about the object, that identify these parameters uniquely. Current approaches are not consistent, i.e., they provide different solutions when run multiple times on the same data. To address this limitation, we propose exploiting local diffuse reflectance (LDR) maxima, i.e., points in the scene where the normal vector is parallel to the illumination direction (see Fig. 1). We demonstrate several noteworthy properties of these maxima: a closed-form solution, computational efficiency and GBR consistency. An LDR maximum yields a simple closed-form solution corresponding to a semi-circle in the GBR parameters space (see Fig. 2); because as few as two diffuse maxima in different images identify a unique solution, the identification of the GBR parameters can be achieved very efficiently; finally, the algorithm is consistent as it always returns the same solution given the same data. Our algorithm is also remarkably robust: It can obtain an accurate estimate of the GBR parameters even with extremely high levels of outliers in the detected maxima (up to 80 % of the observations). The method is validated on real data and achieves state-of-the-art results.

A robust reference signal generator for synchronized ventricular assist devices

Ventricular assist devices (VADs) are blood pumps that offer an option to support the circulation of patients with severe heart failure. Since a failing heart has a remaining pump function, its interaction with the VAD influences the hemodynamics. Ideally, the heart's action is taken into account for actuating the device such that the device is synchronized to the natural cardiac cycle. To realize this in practice, a reliable real-time algorithm for the automatic synchronization of the VAD to the heart rate is required. This paper defines the tasks such an algorithm needs to fulfill: the automatic detection of irregular heart beats and the feedback control of the phase shift between the systolic phases of the heart and the assist device. We demonstrate a possible solution to these problems and analyze its performance in two steps. First, the algorithm is tested using the MIT-BIH arrhythmia database. Second, the algorithm is implemented in a controller for a pulsatile and a continuous-flow VAD. These devices are connected to a hybrid mock circulation where three test scenarios are evaluated. The proposed algorithm ensures a reliable synchronization of the VAD to the heart cycle, while being insensitive to irregularities in the heart rate.

Wie robust sind Arbeitsbeziehung und Therapieerfolg ineinander verzahnt? Eine metaanalytische Bestandsaufnahme

Hintergrund: Die therapeutische Arbeitsbeziehung (alliance) ist das meistuntersuchte Prozessmerkmal in der Psychotherapieforschung schlecht hin und zeigt sich als robuster Prädiktor für Therapieerfolg (r = .275). Fragestellung: Welche Einflussfaktoren (wie beispielsweise kognitive Verhaltenstherapie in randomisierten Trials) moderieren den Zusammenhang zwischen Allianz und Erfolg? Methode: Basierend auf über zweihundert in Englisch, deutsch, französisch und italienisch verfassten Primärstudien werden mögliche Moderatoren metaanalytisch untersucht, die den Zusammenhang zwischen Allianz und Therapieerfolg beeinflussen. Resultate: Der aktuelle Stand der APA-Taskforce kann folgendermaßen zusammengefasst werden: (a) Erhebungszeitpunkt der Allianz, (b) Anzahl Patienten pro Therapeut, (b) Forscherinteresse, (c) Therapieerfolg = Abbrüche, (d) Anteil der Nicht-Weißen Bevölkerung und (e) Alkohol und -Substanzmissbrauch als Ausschlusskriterium, beeinflussen den Zusammenhang zwischen Allianz und Erfolg. Folgenden Aspekten moderieren den Zusammenhang zwischen Allianz und Therapieerfolg nicht: (a) Allianz-Messmittel und Erhebungsperspektive (Patient, Therapeut oder Beobachter), (b) Doktorarbeiten, (c) Therapietradition (Kognitive-Behaviorale, Interpersonale, psychodynamische Therapien), (d) randomisiert kontrollierte Trials, (e) manualisierte Therapien, (f ) störungsspezifische Erfolgsmessung, (g) Persönlichkeitsstörungen, (h) nicht-englisch sprachliche Manuskripte. Diskussion: Durch die Moderatoren kann ein beträchtlicher Anteil der Heterogenität erklärt werden. Die Beziehung zwischen Allianz und Therapieerfolg wird durch konzeptuelle biopsychosozialer Faktoren mitbeeinflusst.

Robust estimates of climate-induced hydrological change in a temperate mountainous region

A sustainable water resources management depends on sound information about the impacts of climate change. This information is, however, not easily derived because natural runoff variability interferes with the climate change signal. This study presents a procedure that leads to robust estimates of magnitude and Time Of Emergence (TOE) of climate-induced hydrological change that also account for the natural variability contained in the time series. Firstly, natural variability of 189 mesoscale catchments in Switzerland is sampled for 10 ENSEMBLES scenarios for the control (1984–2005) and two scenario periods (near future: 2025–2046, far future: 2074–2095) applying a bootstrap procedure. Then, the sampling distributions of mean monthly runoff are tested for significant differences with the Wilcoxon-Mann–Whitney test and for effect size with Cliff’s delta d. Finally, the TOE of a climate change induced hydrological change is determined when at least eight out of the ten hydrological projections significantly differ from natural variability. The results show that the TOE occurs in the near future period except for high-elevated catchments in late summer. The significant hydrological projections in the near future correspond, however, to only minor runoff changes. In the far future, hydrological change is statistically significant and runoff changes are substantial. Temperature change is the most important factor determining hydrological change in this mountainous region. Therefore, hydrological change depends strongly on a catchment’s mean elevation. Considering that the hydrological changes are predicted to be robust in the near future highlights the importance of accounting for these changes in water resources planning.

Robust meta-analytic-predictive priors in clinical trials with historical control information.

Historical information is always relevant for clinical trial design. Additionally, if incorporated in the analysis of a new trial, historical data allow to reduce the number of subjects. This decreases costs and trial duration, facilitates recruitment, and may be more ethical. Yet, under prior-data conflict, a too optimistic use of historical data may be inappropriate. We address this challenge by deriving a Bayesian meta-analytic-predictive prior from historical data, which is then combined with the new data. This prospective approach is equivalent to a meta-analytic-combined analysis of historical and new data if parameters are exchangeable across trials. The prospective Bayesian version requires a good approximation of the meta-analytic-predictive prior, which is not available analytically. We propose two- or three-component mixtures of standard priors, which allow for good approximations and, for the one-parameter exponential family, straightforward posterior calculations. Moreover, since one of the mixture components is usually vague, mixture priors will often be heavy-tailed and therefore robust. Further robustness and a more rapid reaction to prior-data conflicts can be achieved by adding an extra weakly-informative mixture component. Use of historical prior information is particularly attractive for adaptive trials, as the randomization ratio can then be changed in case of prior-data conflict. Both frequentist operating characteristics and posterior summaries for various data scenarios show that these designs have desirable properties. We illustrate the methodology for a phase II proof-of-concept trial with historical controls from four studies. Robust meta-analytic-predictive priors alleviate prior-data conflicts ' they should encourage better and more frequent use of historical data in clinical trials.

Etomidate - a review of robust evidence for its use in various clinical scenarios

Etomidate is an intravenous hypnotic with a favourable clinical profile in haemodynamic high-risk scenarios. Currently, there is an active debate about the clinical significance of the drug's side effects and its overall risk-benefit ratio. Etomidate-induced transient adrenocortical suppression is well documented and has been associated with increased mortality in sepsis. In surgical patients at risk of hypotensive complications, however, a review of current literature provides no robust evidence to contraindicate a single-bolus etomidate induction. Large randomised controlled trials as well as additional observational data are required to compare safety of etomidate and its alternatives.

Efficient and Robust Host–Guest Antenna Composite for Light Harvesting

We report discovery of a new efficient and robust antenna composite for light harvesting. The organic dye hostasol red (HR) is strongly luminescent in aprotic solvents but only weakly luminescent in potassium zeolite L (ZL) at ambient conditions. We observed a dramatic increase of the luminescence quantum yield of HR–ZL composites if some or all exchangeable potassium cations of ZL are substituted by an organic imidazolium cation (IMZ+) and if the acceptor HR is embedded in the middle part of the channels, so that it is fully protected by the environment of the perylene dye tb-DXP. This led to the discovery of a highly efficient donor,acceptor-ZL antenna material where tb-DXP acts as donor and HR acts as acceptor. The material has a donor-to-acceptor (D/A) absorption ratio of more than 100:1 and a nearly quantitative FRET efficiency. Synthesis of this host–guest material is reported. We describe a successful procedure for achieving full sealing of the ZL channel entrances such that the guests cannot escape. This new material is of great interest for applications in luminescent solar concentrator (LSC) devices because the efficiency killing self-absorption is very low.