3D Imaging from Video and Planar Radiography

International audienceIn this paper we consider dense volumetric modeling of moving samples such as body parts.Most dense modeling methods consider samples observed with a moving X-ray device and cannot easily handle moving samples.We propose a novel method that uses a surface motion capture system associated to a single low-cost/low-dose planar X-ray imaging device for dense in-depth attenuation information.Our key contribution is to rely on Bayesian inference to solve for a dense attenuation volume given planar radioscopic images of a moving sample. The approach enables multiple sources of noise to be considered and takes advantage of limited prior information to solve an otherwise ill-posed problem.Results show that the proposed strategy is able to reconstruct dense volumetric attenuation models from a very limited number of radiographic views over time on simulated and in-vivo data

CT from Motion: Volumetric Capture of Moving Shapes with X-rays and Videos

International audienceIn this paper, we consider the capture of dense volumetric X-ray attenuation models of non-rigidly moving samples. Traditional 3D medical imaging apparatus, e.g. CT or MRI, do not easily adapt to shapes that deform significantly such as a moving hand. We propose an approach that simultaneously recovers dense volumetric shape and motion information by combining video and X-ray modalities. Multiple colour images are captured to track shape surfaces while a single X-ray device is used to infer inner attenu-ations. The approach does not assume prior models which makes it versatile and easy to generalise over different shapes. Results on synthetic and real-life data are presented that demonstrate the approach feasibility with a limited number of X-ray views. The resulting dense 4D attenuation data provides unprecedented insights for motion analysis

Video-based methodology for markerless human motion analysis

International audienceThis study presents a video-based experiment for the study of markerless human motion. Silhouettes are extracted from a multi-camera video system to reconstruct a 3D mesh for each frame using a reconstruction method based on visual hull. For comparison with traditional motion analysis results, we set up an experiment integrating video recordings from 8 video cameras and a marker-based motion capture system (Vicon™). Our preliminary data provided distances between the 3D trajectories from the Vicon system and the 3D mesh extracted from the video cameras. In the long term, the main ambition of this method is to provide measurement of skeleton motion for human motion analyses while eliminating markers

Video-based methodology for markerless human motion analysis

International audienceThis study presents a video-based experiment for the study of markerless human motion. Silhouettes are extracted from a multi-camera video system to reconstruct a 3D mesh for each frame using a reconstruction method based on visual hull. For comparison with traditional motion analysis results, we set up an experiment integrating video recordings from 8 video cameras and a marker-based motion capture system (Vicon™). Our preliminary data provided distances between the 3D trajectories from the Vicon system and the 3D mesh extracted from the video cameras. In the long term, the main ambition of this method is to provide measurement of skeleton motion for human motion analyses while eliminating markers

Structure Learning for Activity Recognition in Robot Assisted Intelligent Environments

Abstract-This paper presents a novel structure learning algorithm for the creation of distributed Bayesian networks over static and mobile Vision Sensor Network (VSN) nodes. These compose an assistive, intelligent environment for activity recognition. We provide results demonstrating a higher level of accuracy in the recognition of fine motor tasks when the environment is augmented with a mobile robot and show the ability of our learning algorithm to reduce VSN communication compared to a naïve, greedy structure learning technique. I. INTRODUCTION UE to recent advances in medical care and the adoption of increasingly healthy lifestyles, we are witnessing a demographic shift towards an increasingly aged population Where environments are to contain multiple ambient sensors, installation may be performed by a visiting carer or those living within the domicile. Consequently, it is unreasonable to expect these to be located at optimal locations for the determination of individual activities. Furthermore, since each dwelling is unique, their relative positioning can not be assumed prior to installation thus there is a strong requirement for such networks to be self configuring. To this end, we provide a structure learning algorithm for Bayesian networks which is considerate of both inference and communication cost within ambient Vision Sensor Networks (VSNs). Using Pearl's message propagation algorithm, activity inference can be implemented in a distributed manner over the VSNs, without the requirement for a centralized data repository. Where assistive robots are present, our algorithm can seamlessly incorporate such data to augment recognition accuracy. We demonstrate the efficacy of this algorithm in a home healthcare scenario for fine motor tasks occurring at several locations within the environment. II. RELATED RESEARCH For detecting Activities of Daily Living (ADLs), omnidirectional cameras [6] have previously been employed to capture behavioral patterns in a household environment. For example, a system operating at multiple resolutions has been defined, with a wide angle camera directing the pan, tilt and zoom of other camera

4DHumanOutfit: a multi-subject 4D dataset of human motion sequences in varying outfits exhibiting large displacements

This work presents 4DHumanOutfit, a new dataset of densely sampled spatio-temporal 4D human motion data of different actors, outfits and motions. The dataset is designed to contain different actors wearing different outfits while performing different motions in each outfit. In this way, the dataset can be seen as a cube of data containing 4D motion sequences along 3 axes with identity, outfit and motion. This rich dataset has numerous potential applications for the processing and creation of digital humans, e.g. augmented reality, avatar creation and virtual try on. 4DHumanOutfit is released for research purposes at https://kinovis.inria.fr/4dhumanoutfit/. In addition to image data and 4D reconstructions, the dataset includes reference solutions for each axis. We present independent baselines along each axis that demonstrate the value of these reference solutions for evaluation tasks

Melatonin Promotes Oligodendroglial Maturation of Injured White Matter in Neonatal Rats

OBJECTIVE:To investigate the effects of melatonin treatment in a rat model of white matter damage (WMD) in the developing brain. Additionally, we aim to delineate the cellular mechanisms of melatonin effect on the oligodendroglial cell lineage. METHODS:A unilateral ligation of the uterine artery in pregnant rat at the embryonic day 17 induces fetal hypoxia and subsequent growth restriction (GR) in neonatal pups. GR and control pups received a daily intra-peritoneal injection of melatonin from birth to post-natal day (P) 3. RESULTS:Melatonin administration was associated with a dramatic decrease in microglial activation and astroglial reaction compared to untreated GR pups. At P14, melatonin prevented white matter myelination defects with an increased number of mature oligodendrocytes (APC-immunoreactive) in treated GR pups. Conversely, melatonin was not found to be associated with an increased density of total oligodendrocytes (Olig2-immunoreactive), suggesting that melatonin is able to promote oligodendrocyte maturation but not proliferation. These effects appear to be melatonin-receptor dependent and were reproduced in vitro. INTERPRETATION:These data suggest that melatonin has a strong protective effect on developing damaged white matter through decreased microglial activation and oligodendroglial maturation leading to a normalization of the myelination process. Consequently, melatonin should be a considered as an effective neuroprotective candidate not only in perinatal brain damage but also in inflammatory and demyelinating diseases observed in adults

Neuroprotective Effect of Inhaled Nitric Oxide on Excitotoxic-Induced Brain Damage in Neonatal Rat

BACKGROUND: Inhaled nitric oxide (iNO) is one of the most promising therapies used in neonates. However, little information is known about its impact on the developing brain submitted to excitotoxic challenge. METHODOLOGY/PRINCIPAL FINDINGS: We investigated here the effect of iNO in a neonatal model of excitotoxic brain lesions. Rat pups and their dams were placed in a chamber containing 20 ppm NO during the first week of life. At postnatal day (P)5, rat pups were submitted to intracranial injection of glutamate agonists. At P10, rat pups exposed to iNO exhibited a significant decrease of lesion size in both the white matter and cortical plate compared to controls. Microglia activation and astrogliosis were found significantly decreased in NO-exposed animals. This neuroprotective effect was associated with a significant decrease of several glutamate receptor subunits expression at P5. iNO was associated with an early (P1) downregulation of pCREB/pAkt expression and induced an increase in pAkt protein concentration in response to excitotoxic challenge (P7). CONCLUSION: This study is the first describe and investigate the neuroprotective effect of iNO in neonatal excitotoxic-induced brain damage. This effect may be mediated through CREB pathway and subsequent modulation of glutamate receptor subunits expression

Elaboration, characterization and modelling of new tin dioxide based varistors

Des investigations ont été menées concernant la caractérisation des céramiques semi-conductrices à matrice SnO2, en particulier dans des domaines de densités de courant et de champs électriques élevés. L’ensemble du procédé d’élaboration a été analysé et optimisé, de manière à obtenir des composés aux propriétés électriques aptes à l’application varistance. L’addition de plusieurs dopants a été étudiée, et deux éléments ont donné lieu à un comportement électrique remarquable. Le dopage des grains de SnO2 par l’aluminium (III) permet d’accroître leur conductivité apparente et de ce fait, d’obtenir des composants dont la plage de fonctionnement est équivalente à celle observée pour des varistances ZnO. Le silicium apparaît aux joints de grains dans la microstructure des céramiques. Il réduit fortement la surface effective des joints de grains, entrainant une diminution importante de la zone de fonctionnement des varistances. Simultanément, la caractéristique courant-tension est quasi-idéale avec des coefficients de non-linéarité supérieurs à 100 et des profils de variation similaires à ceux observés pour les diodes Zener. La modélisation du mécanisme de conduction au niveau d’un joint de grain SnO2-SnO2 suggère que ces céramiques présentent un potentiel théorique supérieur aux céramiques à base de ZnO du fait d’une largeur de bande interdite plus importante. Enfin, un comparatif technico-économique succinct a ensuite été proposé, afin d’illustrer la compétitivité des deux matériaux pour l’application varistanceMany investigations have been conducted on semiconductive ceramics with a tin dioxide matrix, particularly in the high electric field and high current density ranges. The sintering process has been optimized, in order to obtain compounds with electrical properties compatible with the varistor application. Among the many dopants studied, two elements produced a remarkable electrical behavior. By doping SnO2 grains with Aluminium (III) allows an increase of their apparent conductivity and hence, widens the working range of tin oxide based compounds, up to the ZnO varistors ones. It appears that the silicium is located on the grain boundaries in the ceramic microstructure. This element reduces strongly the effective surface of the grain boundaries and causes an important diminution of the varistors working range. Simultaneously, the current-voltage behavior appears to be like those observed for a Zener diode, with non-linearity coefficients higher than 100 and nearly ideal variation profiles. The conduction modelling in the SnO2-SnO2 grain boundary area reflects that these ceramics present theoretically a higher potential than ZnO based ceramics, due to a wider SnO2 bandgap. A brief technico-economical comparison has been proposed in order to highlight the competitiveness between the two materials for the varistor application