Adaptive background modeling for land and water composition scenes

Zhao, Jing (Jane); Pang, Shaoning; Hartill, B.; Sarrafzadeh, Hossein

Thumbnail
Share
View fulltext online
Date
2015-09
Citation:
Zhao, J., Pang, S., Hartill. B., & Sarrafzadeh, A. (2015, September). Adaptive Background Modeling for Land and Water Composition Scenes. Vittorio Murino, Enrico Puppo, Gianni Vernazza (Ed.),18th International Conference on Image Analysis and Processing, ICIAP2015 (pp.200-211).
Permanent link to Research Bank record:
https://hdl.handle.net/10652/3359
Abstract
In the context of maritime boat ramps surveillance, this paper proposes an Adaptive Background Modeling method for Land and Water composition scenes (ABM-lw) to interpret the traffic of boats passing across boat ramps. We compute an adaptive learning rate to account for changes on land and water composition scenes, in which the portion of water changes over time due to tidal dynamics and other environmental influences. Experimental comparative tests and quantitative performance evaluations of real-world boat-flow monitoring traffic sequences demonstrate the benefits of the proposed algorithm.
Keywords:
marine traffic, marine boat ramps, moving object detection, background modelling, land and water composition scene, dynamic learning rate
ANZSRC Field of Research:
080110 Simulation and Modelling
Copyright Holder:
International Conference on Image Analysis and Processing (ICIAP)

Copyright Notice:
All rights reserved
Available Online at:
http://www.iciap2015.eu/
Rights:
This digital work is protected by copyright. It may be consulted by you, provided you comply with the provisions of the Act and the following conditions of use. These documents or images may be used for research or private study purposes. Whether they can be used for any other purpose depends upon the Copyright Notice above. You will recognise the author's and publishers rights and give due acknowledgement where appropriate.
Metadata
Show detailed record
This item appears in