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LACBoost and FisherBoost: Optimally Building Cascade Classifiers
[article]
2010
arXiv
pre-print
Object detection is one of the key tasks in computer vision. The cascade framework of Viola and Jones has become the de facto standard. A classifier in each node of the cascade is required to achieve extremely high detection rates, instead of low overall classification error. Although there are a few reported methods addressing this requirement in the context of object detection, there is no a principled feature selection method that explicitly takes into account this asymmetric node learning
arXiv:1005.4103v1
fatcat:jaacgpwvlfa7bnzwc2q44m7cju