Learning cascaded shared-boost classifiers for part-based object detection

This paper focuses on the problem of detecting a number of different class objects in images. We present a novel part-based model for object detection with cascaded classifiers. The coarse root and fine part classifiers are combined into the model. Different from the existing methods which learn roo...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 23(2014), 4 vom: 13. Apr., Seite 1858-71
1. Verfasser:	Yali Li (VerfasserIn)
Weitere Verfasser:	Shengjin Wang, Qi Tian, Xiaoqing Ding
Format:	Online-Aufsatz
Sprache:	English
Veröffentlicht:	2014
Zugriff auf das übergeordnete Werk:	IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Schlagworte:	Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.