Semantic Segmentation of Urban Scenes Using Dense Depth Maps

@inproceedings{Zhang2010SemanticSO,
  title={Semantic Segmentation of Urban Scenes Using Dense Depth Maps},
  author={Chenxi Zhang and Liang Wang and Ruigang Yang},
  booktitle={ECCV},
  year={2010}
}
In this paper we present a framework for semantic scene parsing and object recognition based on dense depth maps. Five viewindependent 3D features that vary with object class are extracted from dense depth maps at a superpixel level for training a classifier using randomized decision forest technique. Our formulation integrates multiple features in a Markov Random Field (MRF) framework to segment and recognize different object classes in query street scene images. We evaluate our method both… CONTINUE READING
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