Systems, methods, and apparatus are described that that increase computer vision analysis in the field of semantic segmentation. With images accompanied by scan data, both two-dimensional and three-dimensional image information is employed for joint segmentation. Through the established correspondence between image data and scan data, two-dimensional and three-dimensional information respectively associated therewith is integrated. Using trained random forest classifiers, the probability of each pixel in images belonging to different object classes is predicted. With the predicted probability, optimization of the labeling of images and scan data is performed by integrating multiples cues in the markov random field.
Joint semantic segmentation of images and scan data