The Visual Social Distancing Problem

One of the main and most effective measures to contain the recent viral outbreak is the maintenance of the so-called Social Distancing (SD). To comply with this constraint, workplaces, public institutions, transports and schools will likely adopt restrictions over the minimum inter-personal distance between people. Given this actual scenario, it is crucial to massively measure the compliance to such physical constraint in our life, in order to figure out the reasons of the possible breaks of such distance limitations, and understand if this implies a possible threat given the scene context. All of this, complying with privacy policies and making the measurement acceptable. To this end, we introduce the Visual Social Distancing (VSD) problem, defined as the automatic estimation of the inter-personal distance from an image, and the characterization of the related people aggregations. VSD is pivotal for a non-invasive analysis to whether people comply with the SD restriction, and to provide statistics about the level of safety of specific areas whenever this constraint is violated. We then discuss how VSD relates with previous literature in Social Signal Processing and indicate which existing Computer Vision methods can be used to manage such problem. We conclude with future challenges related to the effectiveness of VSD systems, ethical implications and future application scenarios.Comment: 9 pages, 5 figures. All the authors equally contributed to this manuscript and they are listed by alphabetical order. Under submissio

Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age

Simultaneous Localization and Mapping (SLAM)consists in the concurrent construction of a model of the environment (the map), and the estimation of the state of the robot moving within it. The SLAM community has made astonishing progress over the last 30 years, enabling large-scale real-world applications, and witnessing a steady transition of this technology to industry. We survey the current state of SLAM. We start by presenting what is now the de-facto standard formulation for SLAM. We then review related work, covering a broad set of topics including robustness and scalability in long-term mapping, metric and semantic representations for mapping, theoretical performance guarantees, active SLAM and exploration, and other new frontiers. This paper simultaneously serves as a position paper and tutorial to those who are users of SLAM. By looking at the published research with a critical eye, we delineate open challenges and new research issues, that still deserve careful scientific investigation. The paper also contains the authors' take on two questions that often animate discussions during robotics conferences: Do robots need SLAM? and Is SLAM solved

Investigating complex networks with inverse models: analytical aspects of spatial leakage and connectivity estimation

Network theory and inverse modeling are two standard tools of applied physics, whose combination is needed when studying the dynamical organization of spatially distributed systems from indirect measurements. However, the associated connectivity estimation may be affected by spatial leakage, an artifact of inverse modeling that limits the interpretability of network analysis. This paper investigates general analytical aspects pertaining to this issue. First, the existence of spatial leakage is derived from the topological structure of inverse operators. Then, the geometry of spatial leakage is modeled and used to define a geometric correction scheme, which limits spatial leakage effects in connectivity estimation. Finally, this new approach for network analysis is compared analytically to existing methods based on linear regressions, which are shown to yield biased coupling estimates.Comment: 19 pages, 4 figures, including 5 appendices; v2: minor edits, 1 appendix added; v3: expanded version, v4: minor edit

Thyroid hormone status within the physiological range affects bone mass and density in healthy men at the age of peak bone mass

Context: The hormonal factors involved in the regulation of peak bone mass (PBM) in men have not been fully investigated. Apart from gonadal steroids and somatotropic hormones, thyroid hormones are known to affect bone maturation and homeostasis and are additional candidate determinants of adult bone mass. Objective: We aimed to investigate between-subject physiological variation in free and total thyroid hormone concentrations, TSH, and thyroid binding globulin (TBG) in relation to parameters of bone mass, geometry, and mineral density in healthy men at the age of PBM. Design and setting: We recruited 677 healthy male siblings aged 25-45 years in a cross-sectional, population-based study. Areal and volumetric bone parameters were determined using dual-energy x-ray absorptiometry (DXA) and peripheral quantitative computed tomography (pQCT). Total and free thyroid hormones, TBG, and TSH were determined using immunoassays. Results: Free and total thyroid hormone concentrations were inversely associated with bone mineral density (BMD) and bone mineral content (BMC) at the hip and total body (free triiodothyronine (FT(3)), total T(3) (TT(3)), and total T(4) (TT(4))) and at the spine (FT(3)). TBG was negatively associated with BMC and areal BMD at all sites. At the radius, cortical bone area was inversely associated with TT(3), TT(4), and TBG, and trabecular bone density was inversely associated with free thyroxine, TT(4), and TBG. We observed inverse associations between cortical bone area at the mid-tibia and FT(3), TT(3), TT(4), and TBG. No associations between TSH and DXA or pQCT measurements were found. Conclusion: In healthy men at the age of PBM, between-subject variation in thyroid hormone concentrations affects bone density, with higher levels of FT(3), TT(3), TT(4), and TBG being associated with less favorable bone density and content

Towards Racially Unbiased Skin Tone Estimation via Scene Disambiguation

Virtual facial avatars will play an increasingly important role in immersive communication, games and the metaverse, and it is therefore critical that they be inclusive. This requires accurate recovery of the appearance, represented by albedo, regardless of age, sex, or ethnicity. While significant progress has been made on estimating 3D facial geometry, albedo estimation has received less attention. The task is fundamentally ambiguous because the observed color is a function of albedo and lighting, both of which are unknown. We find that current methods are biased towards light skin tones due to (1) strongly biased priors that prefer lighter pigmentation and (2) algorithmic solutions that disregard the light/albedo ambiguity. To address this, we propose a new evaluation dataset (FAIR) and an algorithm (TRUST) to improve albedo estimation and, hence, fairness. Specifically, we create the first facial albedo evaluation benchmark where subjects are balanced in terms of skin color, and measure accuracy using the Individual Typology Angle (ITA) metric. We then address the light/albedo ambiguity by building on a key observation: the image of the full scene -- as opposed to a cropped image of the face -- contains important information about lighting that can be used for disambiguation. TRUST regresses facial albedo by conditioning both on the face region and a global illumination signal obtained from the scene image. Our experimental results show significant improvement compared to state-of-the-art methods on albedo estimation, both in terms of accuracy and fairness. The evaluation benchmark and code will be made available for research purposes at https://trust.is.tue.mpg.de.Comment: Camera-Ready version, accepted at ECCV202

Learning, Arts, and the Brain: The Dana Consortium Report on Arts and Cognition

Reports findings from multiple neuroscientific studies on the impact of arts training on the enhancement of other cognitive capacities, such as reading acquisition, sequence learning, geometrical reasoning, and memory

OB Stars in the Solar Neighborhood I: Analysis of their Spatial Distribution

We present a newly-developed, three-dimensional spatial classification method, designed to analyze the spatial distribution of early type stars within the 1 kpc sphere around the Sun. We propose a distribution model formed by two intersecting disks -the Gould Belt (GB) and the Local Galactic Disk (LGD)- defined by their fundamental geometric parameters. Then, using a sample of about 550 stars of spectral types earlier than B6 and luminosity classes between III and V, with precise photometric distances of less than 1 kpc, we estimate for some spectral groups the parameters of our model, as well as single membership probabilities of GB and LGD stars, thus drawing a picture of the spatial distribution of young stars in the vicinity of the Sun.Comment: 28 pages including 9 Postscript figures, one of them in color. Accepted for publication in The Astronomical Journal, 30 January 200