1. A method for generating a classifier configured to automatically label segments of an image, wherein the classifier comprises a first sub-classifier and a second sub-classifier, the method comprising: training a first sub-classifier based on photographic data for a labeled set of image segments and a second sub-classifier based on 3-dimensional (3D) point data for the labeled set of image segments, wherein each of the labeled image segments can be a portion of a larger image partitioned into a plurality of the image segments based on similarity of pixels within the segment and differences with pixels which are outside a boundary of the segment; automatically creating, based on the training, a labeling solution for an unlabeled, second set of image segments by running the first sub-classifier on the second set of image segments and running the second sub-classifier on the second set of image segments, wherein the labeling solution comprises a plurality of associations, each association of the plurality of associations linking an image segment from the set of unlabeled image segments with a label; updating the labeled set of image segments based on the labeling solution, including adding an image segment of the second segments to the labeled set of image segments together with a label having at least one of the associations with the added segment; and retraining the first sub-classifier and the second sub-classifier based on the updated labeled set of image segments.