Robust Real-Time Face Detection
International Journal of Computer Vision
A detector tree of boosted classifiers for real-time object detection and tracking
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1
Accelerated classifier training using the PSL cascading structure
ICONIP'08 Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I
A modular approach to training cascades of boosted ensembles
SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
Adaptive ensemble based learning in non-stationary environments with variable concept drift
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: theory and algorithms - Volume Part I
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We propose a mixed structure to form cascades for AdaBoost classifiers, where parallel strong classifiers are trained for each layer. The structure allows for rapid training and guarantees high hit rates without changing the original threshold. We implemented and tested the approach for two datasets from UCI [1], and compared results of binary classifiers using three different structures: standard AdaBoost, a cascade classifier with threshold adjustments, and the proposed structure.