Accurate, Dense, and Robust Multi-View Stereopsis

@article{Furukawa2007AccurateDA,
  title={Accurate, Dense, and Robust Multi-View Stereopsis},
  author={Yasutaka Furukawa and Jean Ponce},
  journal={2007 IEEE Conference on Computer Vision and Pattern Recognition},
  year={2007},
  pages={1-8}
}
This paper proposes a novel algorithm for calibrated multi-view stereopsis that outputs a (quasi) dense set of rectangular patches covering the surfaces visible in the input images. This algorithm does not require any initialization in the form of a bounding volume, and it detects and discards automatically outliers and obstacles. It does not perform any smoothing across nearby features, yet is currently the top performer in terms of both coverage and accuracy for four of the six benchmark… CONTINUE READING

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