Accessibility navigation


Meeting detection in video through semantic analysis

Patino, L. and Ferryman, J. (2015) Meeting detection in video through semantic analysis. In: 12th IEEE International Conference on Advanced Video- and Signal-based Surveillance (AVSS2015), August 25-28, 2015, Karlsruhe, Germany, pp. 1-6.

[img]
Preview
Text - Accepted Version
· Please see our End User Agreement before downloading.

956kB

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

Official URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?...

Abstract/Summary

In this paper we present a novel approach to detect people meeting. The proposed approach works by translating people behaviour from trajectory information into semantic terms. Having available a semantic model of the meeting behaviour, the event detection is performed in the semantic domain. The model is learnt employing a soft-computing clustering algorithm that combines trajectory information and motion semantic terms. A stable representation can be obtained from a series of examples. Results obtained on a series of videos with different types of meeting situations show that the proposed approach can learn a generic model that can effectively be applied on the behaviour recognition of meeting situations.

Item Type:Conference or Workshop Item (Paper)
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
ID Code:47388

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation