Empirical Analysis of Detection Cascades of Boosted Classifiers for Rapid Object Detection

@inproceedings{Lienhart2003EmpiricalAO,
  title={Empirical Analysis of Detection Cascades of Boosted Classifiers for Rapid Object Detection},
  author={Rainer Lienhart and Alexander Kuranov and Vadim Pisarevsky},
  booktitle={DAGM-Symposium},
  year={2003}
}
Recently Viola et al. have introduced a rapid object detection scheme based on a boosted cascade of simple feature classifiers. In this paper we introduce and empirically analysis two extensions to their approach: Firstly, a novel set of rotated haar-like features is introduced. These novel features significantly enrich the simple features of [6] and can also be calculated efficiently. With these new rotated features our sample face detector shows off on average a 10% lower false alarm rate at… CONTINUE READING
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Key Quantitative Results

  • With these new rotated features our sample face detector shows off on average a 10% lower false alarm rate at a given hit rate.

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