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  author = {Pierre Bouges and
	Thierry Chateau and
	Christophe Blanc and
	Gaƫlle Loosli},
  title = {Handling missing weak classifiers in boosted cascade: application
	to multiview and occluded face detection},
  journal = {{EURASIP} J. Image and Video Processing},
  volume = {2013},
  pages = {55},
  year = {2013},
  url = {https://doi.org/10.1186/1687-5281-2013-55},
  doi = {10.1186/1687-5281-2013-55},
  abstract = {We propose a generic framework to handle missing weak classifiers at testing stage in a boosted cascade. The main contribution is a probabilistic formulation of the cascade structure that considers the uncertainty introduced by missing weak classifiers. This new formulation involves two problems: (1) the approximation of posterior probabilities on each level and (2) the computation of thresholds on these probabilities to make a decision. Both problems are studied, and several solutions are proposed and evaluated. The method is then applied to two popular computer vision applications: detecting occluded faces and detecting faces in a pose different than the one learned. Experimental results are provided using conventional databases to evaluate the proposed strategies related to basic ones.}