Capturing Hand-Object Interaction and Reconstruction of Manipulated Objects

Hand motion capture with an RGB-D sensor gained recently a lot of research attention, however, even most recent approaches focus on the case of a single isolated hand. We focus instead on hands that interact with other hands or with a rigid or articulated object. Our framework successfully captures motion in such scenarios by combining a generative model with discriminatively trained salient points, collision detection and physics simulation to achieve a low tracking error with physically plausible poses. All components are unified in a single objective function that can be optimized with standard optimization techniques. We initially assume a-priori knowledge of the object’s shape and skeleton. In case of unknown object shape there are existing 3d reconstruction methods that capitalize on distinctive geometric or texture features. These methods though fail for textureless and highly symmetric objects like household articles, mechanical parts or toys. We show that extracting 3d hand motion for in-hand scanning e↵ectively facilitates the reconstruction of such objects and we fuse the rich additional information of hands into a 3d reconstruction pipeline. Finally, although shape reconstruction is enough for rigid objects, there is a lack of tools that build rigged models of articulated objects that deform realistically using RGB-D data. We propose a method that creates a fully rigged model consisting of a watertight mesh, embedded skeleton and skinning weights by employing a combination of deformable mesh tracking, motion segmentation based on spectral clustering and skeletonization based on mean curvature flow

The Lag Structure and the General Effect of Ozone Exposure on Pediatric Respiratory Morbidity

Up to now no study has investigated the lag structure of children’s respiratory morbidity due to surface ozone. In the present study, we investigate the lag structure and the general effect of surface ozone exposure on children and adolescents’ respiratory morbidity using data from a particularly well suited area in southern Europe to assess the health effects of surface ozone. The effects of surface ozone are estimated using the recently developed distributed lag non-linear models, allowing for a relatively long timescale, while controlling for weather effects, a range of other air pollutants, and long and short term patterns. The public health significance of the estimated effects is higher than has been previously reported in the literature, providing evidence contrary to the conjecture that the surface ozone-morbidity association is mainly due to short-term harvesting. In fact, our data analysis reveals that the effects of surface ozone at medium and long timescales (harvesting-resistant) are substantially larger than the effects at shorter timescales (harvesting-prone), a finding that is consistent with all children and adolescents being affected by high surface ozone concentrations, and not just the very frail