Conference proceeding
COOPERATIVE SURVEILLANCE IN VIDEO SENSOR NETWORKS
2008 SECOND ACM/IEEE INTERNATIONAL CONFERENCE ON DISTRIBUTED SMART CAMERAS, pp.116-123
01 Jan 2008
Abstract
In the energy-constrained medium of video sensor networks, the objective of much research has been to statistically minimize the number of nodes that will achieve a sufficient degree of coverage. We consider increasing the number of nodes beyond the threshold of full coverage, and cooperatively filtering out the high level of redundant data in the video streams to minimize pernode capacity requirements. The scenario we study is that of a swarm of robots, all with wireless communication capabilities. Some of the robots are equipped with video cameras and are thus considered sensors. A few select robots have sufficient battery and computational power to perform machine vision processing of the video stream. The goal of this scenario is to get the video from the sensors to the video-processing robots, which can then extract high-level surveillance information about the observed environment. We present an optimization framework for minimizing redundant visual data transmissions, while maximizing the throughput from sensors to processing nodes. We also characterize through simulation the performance gain on the sensor network as the video coverage increases.
Metrics
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Details
- Title
- COOPERATIVE SURVEILLANCE IN VIDEO SENSOR NETWORKS
- Creators
- Alex Fridman - Drexel UniversityRichard Primerano - Drexel Univ, Philadelphia, PA 19104 USASteven Weber - Drexel UniversityMoshe Kam - Drexel Univ, Philadelphia, PA 19104 USAIEEE
- Publication Details
- 2008 SECOND ACM/IEEE INTERNATIONAL CONFERENCE ON DISTRIBUTED SMART CAMERAS, pp.116-123
- Conference
- 2008 SECOND ACM/IEEE INTERNATIONAL CONFERENCE ON DISTRIBUTED SMART CAMERAS
- Publisher
- IEEE
- Number of pages
- 8
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering; Mechanical Engineering and Mechanics
- Identifiers
- 991019170387804721
InCites Highlights
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- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Theory & Methods
- Engineering, Electrical & Electronic