Abstract
This paper addresses the problem of excessively long classifier training times associated with using the Adaboost algorithm within the framework of a cascade of boosted ensembles (CoBE). We present new test results confirming the acceleration of the training phase and the robustness of the Parallel Strong classifier within the same Layer (PSL) training structure recently proposed by [1]. The findings demonstrate a speed up of an order of magnitude over the current training methods without a compromise in accuracy. We also present a modified version of the PSL training structure that further decreases the duration of the training phase while preserving accuracy.
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Barczak, A.L.C., Johnson, M.J., Messom, C.H.: Empirical evaluation of a new structure for adaboost. In: SAC 2008: Proceedings of the, ACM symposium on Applied computing, Fortaleza, Ceara, Brazil, pp. 1764–1765. ACM, New York (2008)
Viola, P., Jones, M.: Robust real-time face detection. International Journal of Computer Vision 57, 137–154 (2004)
Verschae, R., del Solar, J.R., Correa, M.: A unified learning framework for object detection and classification using nested cascades of boosted classifiers. Mach. Vision Appl. 19(2), 85–103 (2008)
McCane, B., Novins, K.: On training cascade face detectors. In: Image and Vision Computing, New Zealand, Palmerston North, pp. 239–244 (2003)
Viola, P., Jones, M.J., Snow, D.: Detecting pedestrians using patterns of motion and appearance. In: ICCV, pp. 734–741 (2003)
Withopf, D., Jahne, B.: Improved training algorithm for tree-like classifiers and its application to vehicle detection. In: Jahne, B. (ed.) Proc. IEEE Intelligent Transportation Systems Conference ITSC 2007, pp. 642–647 (2007)
Brubaker, S.C., Mullin, M.D., Rehg, J.M.: Towards optimal training of cascaded detectors. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3951, pp. 325–337. Springer, Heidelberg (2006)
Wu, J., Rehg, J.M., Mullin, M.D.: Learning a rare event detection cascade by direct feature selection. In: NIPS (Advances in Neural Information Processing Systems), Vancouver, Canada (2003)
Freund, Y., Schapire, R.E.: A short introduction to boosting. Journal of Japanese Society for Artificial Intelligence 14(5), 771–780 (1999)
Zhang, C., Viola, P.: Multiple-instance pruning for learning efficient cascade detectors. In: NIPS 2007 (December 2007)
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Susnjak, T., Barczak, A.L.C. (2009). Accelerated Classifier Training Using the PSL Cascading Structure. In: Köppen, M., Kasabov, N., Coghill, G. (eds) Advances in Neuro-Information Processing. ICONIP 2008. Lecture Notes in Computer Science, vol 5506. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02490-0_115
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DOI: https://doi.org/10.1007/978-3-642-02490-0_115
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02489-4
Online ISBN: 978-3-642-02490-0
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