Multiscaled hybrid features generation for AdaBoost object detection

• Autorzy: Dembski J.
• Języki publikacji: EN

Abstrakty

EN

This work presents the multiscaled version of modified census features in graphical objects detection with AdaBoost cascade training algorithm. Several experiments with face detector training process demonstrate better performance of such features over ordinal census and Haar-like approaches. The possibilities to join multiscaled census and Haar features in single hybrid cascade of strong classifiers are also elaborated and tested. The high resolution example images were used in detector training process.

Słowa kluczowe

EN

object detection; machine learning; biometrics; AdaBoost classifier; high resolution images

PL

detekcja obiektów; uczenie maszynowe; biometria; klasyfikator AdaBoost; obrazy wysokiej rozdzielczości

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2015
• Tom: Vol. 24
• Strony: 75--82
• Opis fizyczny: Bibliogr. 15 poz., rys., tab., wykr.

Twórcy

autor

Dembski J.

• Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, ul. Narutowicza 11/12, 80-952 Gdansk, Poland

Bibliografia

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