A clustering unit (101) divides an input three-dimensional point cloud into a plurality of clusters and outputs cluster data, a surrounding point sampling unit (102) extracts, for each of the plurality of clusters, a surrounding three-dimensional point cloud present within a predetermined distance of the cluster based on the three-dimensional point cloud and the cluster data, a learning unit (103) receives, as inputs, extended cluster data including information on a three-dimensional point cloud included in each cluster obtained by the division and information on the extracted surrounding three-dimensional point cloud and a correct answer label indicative of an object to which the three-dimensional point cloud included in each cluster belongs, and learns a parameter of a DNN for estimating a label of each cluster from the extended cluster data, and an estimation unit (104) inputs the extended cluster data related to the cluster of which the label is unknown to the DNN of which the parameter is trained to estimate the label of each cluster.