The Detection of Persons in Cluttered Beach Scenes using Digital Video Imagery and Neural Network-Based Classification
Author(s)
Green, Steven
Blumenstein, Michael
Browne, Matthew
Tomlinson, Rodger
Griffith University Author(s)
Year published
2006
Metadata
Show full item recordAbstract
This paper presents an investigation into the detection and quantification of persons in real-world beach scenes for the automated monitoring of public recreation areas. Aside from the obvious use of video and digital imagery for surveillance applications, this research focuses on the analysis of images for the purpose of predicting trends in the intensity of public usage at beach sites in Australia. The proposed system uses image enhancement and segmentation techniques to detect objects in cluttered scenes. Following these steps, a newly proposed feature extraction technique is used to represent salient information in the ...
View more >This paper presents an investigation into the detection and quantification of persons in real-world beach scenes for the automated monitoring of public recreation areas. Aside from the obvious use of video and digital imagery for surveillance applications, this research focuses on the analysis of images for the purpose of predicting trends in the intensity of public usage at beach sites in Australia. The proposed system uses image enhancement and segmentation techniques to detect objects in cluttered scenes. Following these steps, a newly proposed feature extraction technique is used to represent salient information in the extracted objects for training of a neural network. The neural classifier is used to distinguish the extracted objects between "person" and "non-person" categories to facilitate analysis of tourist activity. Encouraging results are presented for person classification on a database of real-word beach scene images.
View less >
View more >This paper presents an investigation into the detection and quantification of persons in real-world beach scenes for the automated monitoring of public recreation areas. Aside from the obvious use of video and digital imagery for surveillance applications, this research focuses on the analysis of images for the purpose of predicting trends in the intensity of public usage at beach sites in Australia. The proposed system uses image enhancement and segmentation techniques to detect objects in cluttered scenes. Following these steps, a newly proposed feature extraction technique is used to represent salient information in the extracted objects for training of a neural network. The neural classifier is used to distinguish the extracted objects between "person" and "non-person" categories to facilitate analysis of tourist activity. Encouraging results are presented for person classification on a database of real-word beach scene images.
View less >
Journal Title
International Journal of Computational Intelligence and Applications
Volume
6
Issue
2
Copyright Statement
© 2006 Imperial College Press. Self-archiving of the author-manuscript version is not yet supported by this publisher. Please refer to International Journal of Computational Intelligence and Applications for access to the definitive, published version or contact the author for more information.
Subject
Information systems
Information and computing sciences