1. An image segmentation method comprising: generating a hierarchy of regions by unsupervised segmentation of an input image; describing each region of the hierarchy with a respective region multi-dimensional feature vector that is representative of the hierarchy region; identifying triplet hierarchical structures in the hierarchy, each of the triplet hierarchical structures comprising a parent hierarchy region and its respective child hierarchy regions; describing each of the input image triplet hierarchical structures with a respective triplet multi-dimensional feature vector, the triplet multi-dimensional feature vector being generated by aggregating the region multi-dimensional feature vectors of the respective parent hierarchy region and child hierarchy regions of the respective triplet hierarchical structure; with a hierarchical classifier component, classifying each of the input image triplet hierarchical structures according to a set of predefined classes, the hierarchical classifier component having been trained with triplet multi-dimensional feature vectors of triplet hierarchical structures of training images and respective labels of the triplet hierarchical structures of the training images, the training images comprising semantic regions labeled according to the set of predefined classes, the labels of the triplet hierarchical structures of the training images each being a function of the labels of the semantic regions in which pixels of the respective triplet hierarchical structure lie; and segmenting the input image into a plurality of semantic regions based on the classification of the triplet hierarchical structures.