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Lightweight Object Localization with a Single Camera in Wireless Multimedia Sensor Networks
Date
2009-12-04
Author
Oztarak, Hakan
Akkaya, Kemal
Yazıcı, Adnan
Metadata
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This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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Advances in wireless multimedia sensor networks (WMSNs) stimulated interest in designing lightweight solutions in terms of processing and energy consumption for traditional problems due to severe resources constraints on camera sensors. Finding the exact object location is one of such traditional problems which has been well studied in the past. However, the proposed solutions mostly involve complex processing with multiple cameras and thus cannot be applied to surveillance applications which need to be deployed for extended periods. In this paper, we propose an object localization scheme for WMSNs which can be run on a single camera sensor by only using the sensor's location information. Our approach first extracts the detected object using frame differencing. To reduce the processing cost of this operation, each frame size is reduced with some video pre-processing. The location of the object can then be estimated using the distance of the object to the camera and camera/frame size properties. In addition to being energy-efficient, since a single camera sensor is involved, the required time for localization is reduced immensely as opposed to approaches which involve multiple camera sensors. Our experiments indicates that a promising accuracy can be achieved in determining the exact object location without introducing a major energy overhead.
Subject Keywords
Wireless sensor networks
,
Cameras
,
Surveillance
,
Target tracking
,
Batteries
,
Computer networks
,
Design engineering
,
Object detection
,
Costs
,
Image sensors
URI
https://hdl.handle.net/11511/55965
Collections
Department of Computer Engineering, Conference / Seminar
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H. Oztarak, K. Akkaya, and A. Yazıcı, “Lightweight Object Localization with a Single Camera in Wireless Multimedia Sensor Networks,” 2009, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/55965.