Abstract: A computer-implemented method for posture determination is presented. The method includes: a training stage of generating at least one distribution from first pieces of information representing a class of poses of one or more training subjects; and an inference stage including steps of: obtaining at least one second piece of information representing at least one pose of an inference subject; and determining whether the inference subject has a good or bad posture using a statistical anomaly detection technique based on the at least one second piece of information and the at least one distribution.

Abstract: The present disclosure provides a method for processing at least one image comprising inputting the image to at least one neural network, the at least one network being configured to deliver, for each pixel of a group of pixels belonging to an object of a given type visible on the image, an estimation of object parameters that are parameters of the object. The method further comprising processing the estimations of the object parameters using an instance segmentation mask identifying instances of objects having the given type.