Self Calibration of a Sonar-Vision System for Underwater Vehicles: A New Method and a Dataset.

Monocular cameras and multibeam imaging sonars are common sensors of Unmanned Underwater Vehicles (UUV). In this paper, we propose a new method for calibrating a hybrid sonar-vision system. This method is based on motion comparisons between both images and allows us to compute the transformation matrix between the camera and the sonar and to estimate the camera's focal length. The main advantage of our method lies in performing the calibration without any specific calibration pattern, while most other existing methods use physical targets. In this paper, we also propose a new sonar-vision dataset and use it to prove the validity of our calibration method.

Tracking Rift Valley fever: From Mali to Europe and other countries, 2016.

On 16 September 2016, the World Health Organization confirmed a Rift Valley fever (RVF) outbreak in Niger. Epidemiological surveillance was reinforced among the French Armed Forces deployed in Niger and bordering countries: Chad, Mali and Burkina Faso. On 26 October, a probable case of RVF was reported in a service member sampled in Mali 3 weeks earlier. At the time the result was reported, the patient was on vacation on Martinique. An epidemiological investigation was conducted to confirm this case and identify other cases. Finally, the case was not confirmed, but three suspected cases of RVF were confirmed using serological and molecular testing. RVF viral RNA was detectable in whole blood for 57 and 67 days after onset of symptoms for two cases, although it was absent from plasma and serum. At the time of diagnosis, these cases had already returned from Mali to Europe. The infectivity of other arboviruses in whole blood has already been highlighted. That RVF virus has been detected in whole blood that long after the onset of symptoms (67 days) raises the question of its potential prolonged infectivity. Because of exposure to tropical infectious diseases during deployment, military populations could import emerging pathogens to Europe.

Non-Additive Imprecise Image Super-Resolution in a Semi-Blind Context.

The most effective superresolution methods proposed in the literature require precise knowledge of the so-called point spread function of the imager, while in practice its accurate estimation is nearly impossible. This paper presents a new superresolution method, whose main feature is its ability to account for the scant knowledge of the imager point spread function. This ability is based on representing this imprecise knowledge via a non-additive neighborhood function. The superresolution reconstruction algorithm transfers this imprecise knowledge to output by producing an imprecise (interval-valued) high-resolution image. We propose some experiments illustrating the robustness of the proposed method with respect to the imager point spread function. These experiments also highlight its high performance compared with very competitive earlier approaches. Finally, we show that the imprecision of the high-resolution interval-valued reconstructed image is a reconstruction error marker.