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Boosting Algorithms for Detector Cascade learning

JOURNAL OF MACHINE learning RESEARCH 2014年第7期15卷 2569-2605页

作者： Saberian, Mohammad Vasconcelos, Nuno Univ Calif San Diego Stat Visual Comp Lab La Jolla CA 92039 USA

The problem of learning classifier cascades is considered. A new cascade boosting algorithm, fast cascade boosting (FCBoost), is proposed. FCBoost is shown to have a number of interesting properties, namely that it 1) minimizes a Lagrangian risk that jointly accounts for classification accuracy and speed, 2) generalizes adaboost, 3) can be made cost-sensitive to support the design of high detection rate cascades, and 4) is compatible with many predictor structures suitable for sequential decision making. It is shown that a rich family of such structures can be derived recursively from cascade predictors of two stages, denoted cascade generators. Generators are then proposed for two new cascade families, last-stage and multiplicative cascades, that generalize the two most popular cascade architectures in the literature. The concept of neutral predictors is finally introduced, enabling FCBoost to automatically determine the cascade configuration, i.e., number of stages and number of weak learners per stage, for the learned cascades. Experiments on face and pedestrian detection show that the resulting cascades outperform current state-of-the-art methods in both detection accuracy and speed.

关键词： complexity-constrained learning detector cascades sequential decision-making boosting ensemble methods cost-sensitive learning real-time object detection

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Boosting algorithms for detector cascade learning

The Journal of Machine Learning Research

引用

The Journal of Machine learning Research 2014年第1期15卷

作者： Kevin Murphy Bernhard Schölkopf Mohammad Saberian Nuno Vasconcelos Google Statistical Visual Computing Laboratory University of California San Diego La Jolla CA

关键词： boosting complexity-constrained learning cost-sensitive learning detector cascades ensemble methods real-time object detection sequential decision-making

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