Automatic Annotation for Semantic Segmentation in Indoor Scenes

Md Alimoor Reza; Akshay U. Naik; Kai Chen; David J. Crandall

IROS 2019poster8 citations

Automatic Annotation for Semantic Segmentation in Indoor Scenes

Md Alimoor Reza, Akshay U. Naik, Kai Chen, David J. Crandall

Abstract

Domestic robots could eventually transform our lives, but safely operating in home environments requires a rich understanding of indoor scenes. Learning-based techniques for scene segmentation require large-scale, pixel-level annotations, which are laborious and expensive to collect. We propose an automatic method for pixel-wise semantic annotation of video sequences, that gathers cues from object detectors and indoor 3D room-layout estimation and then annotates all the image pixels in an energy minimization framework. Extensive experiments on a publicly available video dataset (SUN3D) evaluate the approach and demonstrate its effectiveness.

BibTeX

@inproceedings{iros2019_automaticannotat,
  title = {Automatic Annotation for Semantic Segmentation in Indoor Scenes},
  author = {Md Alimoor Reza and Akshay U. Naik and Kai Chen and David J. Crandall},
  booktitle = {IROS 2019},
  year = {2019}
}