In the paper, we analyze the problem of automatic room floor segmentation. For this purpose, we consider several classic computer vision algorithms as well as some of the deep convolutional neural network architectures. The segmentation results are illustrated and compared. An idea for combining two groups of methods is proposed. It is demonstrated that a proper fusion provides the best segmentation quality.

Comparative Analysis of Classic Computer Vision Methods and Deep Convolutional Neural Networks for Floor Segmentation