Abstract: Provided is a pose estimation method in a 3D pose estimation apparatus for estimating a 3D pose of an object based on a graph convolution network (GCN). The pose estimation method comprises inputting a feature vector for a joint of the object; generating an affinity matrix according to the feature vector; generating a dynamic graph matrix by fusing the affinity matrix with a predefined static graph matrix of the graph convolution network; and estimating a 3D pose of the object for the feature vector by replacing the static graph matrix of the graph convolution network with the dynamic graph matrix. As a result, the performance of estimating a 3D pose can be greatly improved while almost maintaining the memory usage and inference time of the existing graph convolution network (GCN).

Abstract: Provided is a system and method for automatically providing content in access areas based on access points, in which when a user enters an area in which an access point is installed, content corresponding to the content providing area is automatically provided to a terminal of the user.