Hybrid object recognition in image sequences

被引：0

作者：

Kummert, F ^{[1
]}

Fink, GA ^{[1
]}

Sagerer, G ^{[1
]}

Braun, E ^{[1
]}

机构：

[1] Univ Bielefeld, Fak Biol, AG Angew Informat, D-33501 Bielefeld, Germany

来源：

FOURTEENTH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1 AND 2 | 1998年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present a hybrid approach attaching probabilistic formalisms, as artificial neural networks or hidden Markov models, to concepts of a semantic network for a robust and efficient detection of objects. Additionally, an efficient processing strategy for image sequences is outlined which propagates the structural results of the semantic network as an expectation for the next image. This method allows to produce linked results over time supporting the recognition of events and actions.

引用

页码：1165 / 1170

页数：6

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