Abstract: The invention relates to a semi-automatic image segmentation system comprising a neural network (12) configured to receive, at each iteration, input data comprising at least one image (14) to be segmented and to provide output data comprising at least one segmentation mask (16) of each image, characterized in that it further comprises a user interaction loop (18) comprising a user interaction module (20) configured to provide at least one user mask representative of an interaction of a real user and/or of a simulated user on each segmentation mask, said user interaction loop (18) being configured to provide, as input data of the neural network (12), each segmentation mask provided by said neural network coming from a previous iteration of the neural network (12), referred to as past segmentation mask, and the user mask associated with each past segmentation mask.

Abstract: The invention relates to a method for real-time tracking of the placement of a camera with respect to a 3D model comprising a keyframe base comprising a first thread of execution making it possible to estimate the current placement of the camera from a selected keyframe, characterized in that the method further comprises a step of analyzing the quality of the estimation of the placement of the camera from the image stored in a buffer memory, and a step of analyzing the sharpness of the image stored in the buffer memory from data representative of the movement of the camera, and if the quality of the estimation of the placement of the camera from the stored image and the sharpness of the stored image conform to predetermined criteria, a step of adding the image stored in the buffer memory to the keyframe base as a new keyframe.