Multiscaled Hybrid Features Generation for AdaBoost Object Detection

Jerzy Dembski

Multiscaled Hybrid Features Generation for AdaBoost Object Detection

Abstract

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.

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Jerzy Dembski dr inż.

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Category:: Articles
Type:: artykuły w czasopismach recenzowanych i innych wydawnictwach ciągłych
Published in:: Journal of Medical Informatics & Technologies no. 24, pages 75 - 82,
ISSN: 1642-6037
Language:: English
Publication year:: 2015
Bibliographic description:: Dembski J.: Multiscaled Hybrid Features Generation for AdaBoost Object Detection// Journal of Medical Informatics & Technologies. -Vol. 24., (2015), s.75-82
Verified by:: Gdańsk University of Technology