Abstract: A method for generating a human body model includes acquiring at least one partial view of an individual defining a 3D image from at least one optical device arranged in a position of space, and generating a human body model by applying a trained neural network to generate a 3D model of the individual body from input 3D images, the training of the neural network being performed from a set of data describing partial views of the human body.

Abstract: A method for acquiring images of a first surface of a human body using a image capturing device including a variable focus optics, the method including acquisitions of a plurality of images using the image capturing device, the acquisitions being carried out by varying the focal length of the variable focus optics according to a control law; constructing a sharp image of a portion of the surface of the human body from the plurality of images acquired of the surface, and estimating the depth map of the local geometry of the first surface.

Abstract: A method for guiding in real time a robot arm for the processing of data of the surface of a body, includes generating a body model including a meshing of points; planning a treatment trajectory on the surface of the body model with a calculator; activating at least one transmission of a transmitter and/or acquisition of a sensor of an operator device, the operator device being arranged at the distal end of the robotised arm, the activation being carried out when the orientation of the axis of the sensor or the transmitter is merged with a predefined straight line passing through the target point, the target point being referenced on the generated body model.

Abstract: A method for generating a three-dimensional working surface of a human body, includes receiving input data corresponding to geometric data; generating a first point cloud from the input data; generating partial views of parameterised body models corresponding to a parametric body model parameterised with different parameterisation configurations, wherein the parametric body model models the human body in which a set of articulations are predefined; calculating a set of geometric parameters, and determining another parameterised model from the set of geometric parameters to generate the human body model of the human body including a first meshing.

Abstract: A robot device ensuring an automatic guiding of a robotic arm, including a frame holding a robotic arm articulated along axes of freedom, the robotic arm including a distal operator device for generating a human-machine interaction, the robot device further including an image acquisition system including at least two optical devices integral with the frame and arranged in at least two distinct positions of the frame, each optical device configured to acquire a 3D image, the image acquisition system being configured to acquire a plurality of 3D images of a human body of a patient from at least two optical devices, the robot device including a calculation unit for generating in real time a human body model of the patient from the acquired 3D images and a guiding trajectory referenced to the surface of the human body model, wherein movements of the robotic arm are enslaved to the guiding trajectory.

Abstract: A method for generating a three-dimensional working surface of a human body includes receiving input data corresponding to images; generating a first point cloud from the input data, each point being associated with a three-dimensional spatial coordinate; determining a plurality of attributes at each point of the first point cloud, calculating a set of geometric parameters from a regression carried out from a series of matrix operations performed according to different layers of a neural network trained from a plurality of partial views of parametric models parameterised with different parameterisation configurations; determining a parameterised model to generate a body model of a body including a first meshing.