Abstract: A device and a method for recognizing person activity in a sequence of frames (100) comprising: obtaining a set of consecutives 3D poses (103), obtaining a feature map (102), obtaining a vector of spatiotemporal features, obtaining a matrix of spatial attention weights, obtaining a matrix of temporal attention weights (110), modulating (106) the feature map using the matrix of spatial attention weights to obtain a spatially modulated feature map, modulating (111) the feature map using the vector of temporal attention weights to obtain a temporally modulated feature map, performing a convolution (114) of the spatially modulated feature map and of the temporally modulated feature map to obtain a convoluted feature map, performing a classification (115) using the convoluted feature map so as to determine the activity of the person in the video.

Abstract: A grasping points determination method including: S10) receiving a scene image showing an object to be grasped; S20) in the scene image, determine the object and its features, and local descriptors and 2D-locations of these features; S30) based on database local descriptors of features of the object and 2D- and 3D-location(s) of grasping points of the object, determined in a previous position of the object, identifying a best-fit combination which transforms previously defined local descriptors into the determined local descriptors; S40) determining the registration corresponding to the combination; S50) determining in the scene image 2D-location(s) of grasping points by applying registration to previously defined 3D-location(s) of the grasping points; S60) determining 3D information relative to the object; S70) determining 3D-location(s) of the grasping points. Grasping points database creation method for creating the database. Systems for implementing the above methods.

Abstract: A computer-implemented method for monitoring a process to be performed by a person, comprising: obtaining at least one image of the person performing the process; detecting a human pose of the person in the at least one image; detecting at least one object in the at least one image; returning monitoring information on the process based on at least one geometrical relationship between the detected human pose and the detected at least one object.