Unsupervised learning of probabilistic object models (POMs) for object classification, segmentation, and recognition using knowledge propagation

We present a method to learn probabilistic object models (POMs) with minimal supervision, which exploit different visual cues and perform tasks such as classification, segmentation, and recognition. We formulate this as a structure induction and learning task and our strategy is to learn and combine...

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Bibliographische Detailangaben

Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence. - 1979. - 31(2009), 10 vom: 16. Okt., Seite 1747-61
1. Verfasser:	Chen, Yuanhao (VerfasserIn)
Weitere Verfasser:	Zhu, Long Leo, Yuille, Alan, Zhang, Hongjiang
Format:	Online-Aufsatz
Sprache:	English
Veröffentlicht:	2009
Zugriff auf das übergeordnete Werk:	IEEE transactions on pattern analysis and machine intelligence
Schlagworte:	Journal Article Research Support, Non-U.S. Gov't