Automatic design of cascaded classifiers
E Grossmann - Structural, Syntactic, and Statistical Pattern Recognition …, 2004 - Springer
Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR …, 2004•Springer
Cascades of boosted classifiers have become increasingly popular in machine vision and
have generated a lot of recent research. Most of it has focused on modifying the underlying
Adaboost method and far less attention has been given to the problem of dimensioning the
cascade, ie determining the number and the characteristics of the boosted classifiers. To a
large extent, the designer of a cascade must set the parameters in the cascade using ad-hoc
methods. We propose to automatically build a cascade of classifiers, given just a family of …
have generated a lot of recent research. Most of it has focused on modifying the underlying
Adaboost method and far less attention has been given to the problem of dimensioning the
cascade, ie determining the number and the characteristics of the boosted classifiers. To a
large extent, the designer of a cascade must set the parameters in the cascade using ad-hoc
methods. We propose to automatically build a cascade of classifiers, given just a family of …
Abstract
Cascades of boosted classifiers have become increasingly popular in machine vision and have generated a lot of recent research. Most of it has focused on modifying the underlying Adaboost method and far less attention has been given to the problem of dimensioning the cascade, i.e. determining the number and the characteristics of the boosted classifiers. To a large extent, the designer of a cascade must set the parameters in the cascade using ad-hoc methods.
We propose to automatically build a cascade of classifiers, given just a family of weak classifiers a desired performance level and little more. First, a boosted classifier with the desired performance is built using any boosting method. This classifier is then “sliced” using dynamic programming into a cascade of classifiers in a nearly computation-cost-optimal fashion.
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