Unsupervised Feature Learning for RGB-D Based Object Recognition

@inproceedings{Bo2012UnsupervisedFL,
  title={Unsupervised Feature Learning for RGB-D Based Object Recognition},
  author={Liefeng Bo and Xiaofeng Ren and Dieter Fox},
  booktitle={ISER},
  year={2012}
}
Recently introduced RGB-D cameras are capable of providing high quality synchronized videos of both color and depth. With its advanced sensing capabilities, this technology represents an opportunity to dramatically increase the capabilities of object recognition. It also raises the problem of developing expressive features for the color and depth channels of these sensors. In this paper we introduce hierarchical matching pursuit (HMP) for RGB-D data. HMP uses sparse coding to learn hierarchical… CONTINUE READING
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