Generic object recognition with boosting

@article{Opelt2006GenericOR,
  title={Generic object recognition with boosting},
  author={Andreas Opelt and Axel Pinz and Michael Fussenegger and Peter Auer},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2006},
  volume={28},
  pages={416-431}
}
This paper explores the power and the limitations of weakly supervised categorization. We present a complete framework that starts with the extraction of various local regions of either discontinuity or homogeneity. A variety of local descriptors can be applied to form a set of feature vectors for each local region. Boosting is used to learn a subset of such feature vectors (weak hypotheses) and to combine them into one final hypothesis for each visual category. This combination of individual… CONTINUE READING
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