Extraction of semantic description of events using Bayesian networks

被引：0

作者：

Ekin, W ^{[1
]}

Tekalp, AM ^{[1
]}

Mehrotra, R ^{[1
]}

机构：

[1] Univ Rochester, Dept Elect & Comp Engn, Rochester, NY 14627 USA

来源：

2001 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS I-VI, PROCEEDINGS: VOL I: SPEECH PROCESSING 1; VOL II: SPEECH PROCESSING 2 IND TECHNOL TRACK DESIGN & IMPLEMENTATION OF SIGNAL PROCESSING SYSTEMS NEURALNETWORKS FOR SIGNAL PROCESSING; VOL III: IMAGE & MULTIDIMENSIONAL SIGNAL PROCESSING MULTIMEDIA SIGNAL PROCESSING | 2001年

关键词：

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

In this paper, we use Bayesian belief networks to sta- tistically model the trends for event detection. We automatically detect non-rigid object trajectories for object motion units. Then, we use dominant and secondary trajectories of a single object in several consecutive motion unite, to understand semantic actions or those of more than one object to recognize semantic interactions between objects. We demonstrate sample Bayesian networks to detect events and extract the event descriptions, such as "catch the ball", "throw the ball" and "walk".

引用

页码：1585 / 1588

页数：4

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