Intrinsic Dynamic Shape Prior for Fast, Sequential and Dense Non-Rigid Structure from Motion with Detection of Temporally-Disjoint Rigidity

While dense non-rigid structure from motion (NRSfM) has been extensively studied from the perspective of the reconstructability problem over the recent years, almost no attempts have been undertaken to bring it into the practical realm. The reasons for the slow dissemination are the severe ill-posedness, high sensitivity to motion and deformation cues and the difficulty to obtain reliable point tracks in the vast majority of practical scenarios. To fill this gap, we propose a hybrid approach that extracts prior shape knowledge from an input sequence with NRSfM and uses it as a dynamic shape prior for sequential surface recovery in scenarios with recurrence. Our Dynamic Shape Prior Reconstruction (DSPR) method can be combined with existing dense NRSfM techniques while its energy functional is optimised with stochastic gradient descent at real-time rates for new incoming point tracks. The proposed versatile framework with a new core NRSfM approach outperforms several other methods in the ability to handle inaccurate and noisy point tracks, provided we have access to a representative (in terms of the deformation variety) image sequence. Comprehensive experiments highlight convergence properties and the accuracy of DSPR under different disturbing effects. We also perform a joint study of tracking and reconstruction and show applications to shape compression and heart reconstruction under occlusions. We achieve state-of-the-art metrics (accuracy and compression ratios) in different scenarios

{IsMo-GAN}: {A}dversarial Learning for Monocular Non-Rigid {3D} Reconstruction

The majority of the existing methods for non-rigid 3D surface regression from monocular 2D images require an object template or point tracks over multiple frames as an input, and are still far from real-time processing rates. In this work, we present the Isometry-Aware Monocular Generative Adversarial Network (IsMo-GAN) - an approach for direct 3D reconstruction from a single image, trained for the deformation model in an adversarial manner on a light-weight synthetic dataset. IsMo-GAN reconstructs surfaces from real images under varying illumination, camera poses, textures and shading at over 250 Hz. In multiple experiments, it consistently outperforms several approaches in the reconstruction accuracy, runtime, generalisation to unknown surfaces and robustness to occlusions. In comparison to the state-of-the-art, we reduce the reconstruction error by 10-30% including the textureless case and our surfaces evince fewer artefacts qualitatively

Ageism in the Workplace: Ageing in the Age of Intolerance

Age discrimination is widespread, but not widely acknowledged. Unlike racism and sexism, ageism is often normalized (WHO, 2020). As people live longer, healthier lives, they also remain in the workplace longer (Bureau of Labor Statistics, 2017). A majority (64%), of older workers, particularly female workers, report being subjected to discriminatory mistreatment (AARP, 2014). This presentation focuses on a discussion of the preliminary results of an ongoing study addressing age discrimination in the workplace. A sample of 244 WCU faculty and staff (ages 20 - 80) responded to an online survey. Questions probed work experiences, work attitudes, stress, and life satisfaction. Forty-six percent (n = 112) of participants reported experiencing ageist treatment; of these, 64 were women, indicating that older women were more likely to face intersectional discrimination (Barrington, 2015). Qualitative data analysis (Braun & Clarke, 2006) indicated that ageist treatment resulted in feelings of powerlessness and isolation. Consequently, older faculty women often lowered their professional expectations and engaged in self-silencing. This presentation addresses the personal, social, and cultural consequences of age discrimination and suggests possible solutions to this widespread problem

Recent Technological Developments on LGAD and iLGAD Detectors for Tracking and Timing Applications

This paper reports the last technological development on the Low Gain Avalanche Detector (LGAD) and introduces a new architecture of these detectors called inverse-LGAD (iLGAD). Both approaches are based on the standard Avalanche Photo Diodes (APD) concept, commonly used in optical and X-ray detection applications, including an internal multiplication of the charge generated by radiation. The multiplication is inherent to the basic n++-p+-p structure, where the doping profile of the p+ layer is optimized to achieve high field and high impact ionization at the junction. The LGAD structures are optimized for applications such as tracking or timing detectors for high energy physics experiments or medical applications where time resolution lower than 30 ps is required. Detailed TCAD device simulations together with the electrical and charge collection measurements are presented through this work.Comment: Keywords: silicon detectors, avalanche multiplication, timing detectors, tracking detectors. 8 pages. 8 Figure

{HandVoxNet}: {D}eep Voxel-Based Network for {3D} Hand Shape and Pose Estimation from a Single Depth Map

3D hand shape and pose estimation from a single depth map is a new and challenging computer vision problem with many applications. The state-of-the-art methods directly regress 3D hand meshes from 2D depth images via 2D convolutional neural networks, which leads to artefacts in the estimations due to perspective distortions in the images. In contrast, we propose a novel architecture with 3D convolutions trained in a weakly-supervised manner. The input to our method is a 3D voxelized depth map, and we rely on two hand shape representations. The first one is the 3D voxelized grid of the shape which is accurate but does not preserve the mesh topology and the number of mesh vertices. The second representation is the 3D hand surface which is less accurate but does not suffer from the limitations of the first representation. We combine the advantages of these two representations by registering the hand surface to the voxelized hand shape. In the extensive experiments, the proposed approach improves over the state of the art by 47.8% on the SynHand5M dataset. Moreover, our augmentation policy for voxelized depth maps further enhances the accuracy of 3D hand pose estimation on real data. Our method produces visually more reasonable and realistic hand shapes on NYU and BigHand2.2M datasets compared to the existing approaches

Cross-verification of independent quantum devices

Quantum computers are on the brink of surpassing the capabilities of even the most powerful classical computers. This naturally raises the question of how one can trust the results of a quantum computer when they cannot be compared to classical simulation. Here we present a verification technique that exploits the principles of measurement-based quantum computation to link quantum circuits of different input size, depth, and structure. Our approach enables consistency checks of quantum computations within a device, as well as between independent devices. We showcase our protocol by applying it to five state-of-the-art quantum processors, based on four distinct physical architectures: nuclear magnetic resonance, superconducting circuits, trapped ions, and photonics, with up to 6 qubits and 200 distinct circuits

Rough paths in idealized financial markets

This paper considers possible price paths of a financial security in an idealized market. Its main result is that the variation index of typical price paths is at most 2, in this sense, typical price paths are not rougher than typical paths of Brownian motion. We do not make any stochastic assumptions and only assume that the price path is positive and right-continuous. The qualification "typical" means that there is a trading strategy (constructed explicitly in the proof) that risks only one monetary unit but brings infinite capital when the variation index of the realized price path exceeds 2. The paper also reviews some known results for continuous price paths and lists several open problems.Comment: 21 pages, this version adds (in Appendix C) a reference to new results in the foundations of game-theoretic probability based on Hardin and Taylor's work on hat puzzle

Lessons to be learned from the coherent photoproduction of pseudoscalar mesons

We study the coherent photoproduction of pseudoscalar mesons---particularly of neutral pions---placing special emphasis on the various sources that put into question earlier nonrelativistic-impulse-approximation calculations. These include: final-state interactions, relativistic effects, off-shell ambiguities, and violations to the impulse approximation. We establish that, while distortions play an essential role in the modification of the coherent cross section, the uncertainty in our results due to the various choices of optical-potential models is relatively small (of at most 30%). By far the largest uncertainty emerges from the ambiguity in extending the many on-shell-equivalent representations of the elementary amplitude off the mass shell. Indeed, relativistic impulse-approximation calculations that include the same pionic distortions, the same nuclear-structure model, and two sets of elementary amplitudes that are identical on-shell, lead to variations in the magnitude of the coherent cross section by up to factors of five. Finally, we address qualitatively the assumption of locality implicit in most impulse-approximation treatments, and suggest that the coherent reaction probes---in addition to the nuclear density---the polarization structure of the nucleus.Comment: Manuscript is 27 pages long and includes 11 eps figure

Using Stakeholder Engagement to Overcome Barriers to Implementing Patient-reported Outcomes (PROs) in Cancer Care Delivery: Approaches From 3 Prospective Studies

Introduction: Patient-reported outcome (PRO) measures used during cancer care delivery improve communication about symptoms between patients and clinicians and reduce service utilization for uncontrolled symptoms. However, uptake of PROs in routine cancer care has been slow. In this paper, we describe stakeholder engagement activities used to overcome barriers to implementing PROs. Implementation occurred in 2 study settings: PROs completed in the waiting room and reviewed during clinical visits to guide symptom management for multiple myeloma (visit-based PROs); and weekly PROs completed by cancer patients between chemotherapy visits to monitor symptoms at home (remote PROs). Methods: PRO implementation steps across studies included: (1) clinician and patient input on key symptoms, PRO measures, and identifying which PRO responses are clinically concerning to better target nursing actions; (2) developing PRO-based clinical decision support (CDS) for responding to concerning PROs; (3) training clinicians and clinical research assistants to interpret PROs and use software; and (4) describing implementation impact (frequency of concerning PRO responses and nursing actions). Discussion: Clinician and patient input was critical for identifying key symptoms, PRO measures, and clinically concerning response options. For the visit-based PRO observational study, all symptom scores appeared on a clinician dashboard, and those rated ≥1 by patients (on a 0–4 or 0–10 scale) had PRO-based CDS available for access. For the 2 remote PROs trials, stakeholders recommended that the 2 “worst” response options (eg, PRO responses of “often”/“always” or “severe”/“very severe”) would trigger an automated email alert to a nurse along with PRO-based CDS. In each study, PRO-based CDS was tailored based on clinician input. Across studies, the most common nursing response to concerning PROs was counseling patients on (or providing care plans for) self-management of symptoms. In the trials, the percentage of weekly remote PROs generating an alert to a nurse ranged from 13% at an academic center to 36% in community oncology practices. Key Points: Across 3 prospective studies, PROs implemented into cancer care enabled tailored care based on issues identified on PROs. Stakeholder engagement was critical for successful implementation. This paper assists in addressing important PRO implementation challenges by describing a stakeholder-driven approach