The TDP-43 target G3BP1 is essential for a functional interaction between stress granules and processing bodies.

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International audience2D visual servoing consists in using data provided by a vision sensor for controlling the motions of a dynamic system. Most of visual servoing approaches has relied on the geometric features that have to be tracked and matched in the image acquired by the camera. Recent works have highlighted the interest of taking into account the photometric information of the entire image. This approach was tackled with images of perspective cameras. We propose, in this paper, to extend this technique to central cameras. This generalization allows to apply this kind of method to catadioptric cameras and wide field of view cameras. Several experiments have been successfully done with a fisheye camera in order to control a 6 degrees of freedom (dof) robot and with a catadioptric camera for a mobile robot navigation task

International audienceThis paper deals with model-based pose estimation (or camera localization). The model is rendered as a virtual image and we propose a direct approach that takes into account the image as a whole. For this, we consider a sim- ilarity measure, the mutual information. Mutual information is a measure of the quantity of information shared by two signals (or two images in our case). Exploiting this measure allows our method to deal with different image modalities (real and synthetic). Furthermore, it handles occlusions and illu- mination changes. Results with synthetic (benchmark) and real image sequences, with static or mobile camera, demonstrate the robustness of the method and its ability to produce stable and precise pose estimations