A survey of RGB-D image semantic segmentation by deep learning

Abstract

The semantic segmentation task one of a popular difficult problem in computer vision. This task takes great attention to the community of computer vision. Semantic segmentation segments the image which is input into meaningful semantically related regions in another expression, it predicates for each pixel inside image a class label, with appears of depth cameras it provides very useful organized rich information of data depth, RGB-D image not related with illumination when a mixed feature of RGB-D images with depth information features can very improve the accuracy of semantic segmentation. Recently, deep learning satisfied semantic segmentation more easily than traditional methods because of neural networks' power to automatically learn different representations of proper features. This paper survey provides a background for several techniques work on 2.D RGB-D dataset semantic segmentation in various applications on several different out and door free datasets.