From Wikipedia, the free encyclopedia
A
visual sensor network
or
smart camera network
or
intelligent camera network
is a network of spatially distributed
smart camera
devices capable of processing, exchanging data and fusing images of a scene from a variety of viewpoints into some form more useful than the individual images.
[1]
[2]
[3]
A visual sensor network may be a type of
wireless sensor network
, and much of the theory and application of the latter applies to the former. The network generally consists of the cameras themselves, which have some local
image processing
, communication and storage capabilities, and possibly one or more central computers, where image data from multiple cameras is further processed and
fused
(this processing may, however, simply take place in a distributed fashion across the cameras and their local controllers). Visual sensor networks also provide some high-level services to the user so that the large amount of data can be distilled into information of interest using specific queries.
[4]
[5]
[6]
The primary difference between visual sensor networks and other types of sensor networks is the nature and volume of information the individual sensors acquire: unlike most
sensors
, cameras are directional in their
field of view
, and they capture a large amount of visual information which may be partially processed independently of data from other cameras in the network. Alternatively, one may say that while most sensors measure some value such as temperature or pressure, visual sensors measure
patterns
. In light of this, communication in visual sensor networks differs substantially from traditional sensor networks.
Applications
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]
Visual sensor networks are most useful in applications involving area
surveillance
,
tracking
, and
environmental monitoring
. Of particular use in surveillance applications is the ability to perform a dense 3D reconstruction of a scene and storing data over a period of time, so that operators can view events as they unfold over any period of time (including the current moment) from any arbitrary viewpoint in the covered area, even allowing them to "fly" around the scene in real time. High-level analysis using
object recognition
and other techniques can intelligently track objects (such as people or cars) through a scene, and even determine what they are doing so that certain activities could be automatically brought to the operator's attention. Another possibility is the use of visual sensor networks in telecommunications, where the network would automatically select the "best" view (perhaps even an arbitrarily generated one) of a live event.
See also
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]
References
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edit
]
- ^
Tavli, Bulent; Bicakci, Kemal; Zilan, Ruken; Barcelo-Ordinas, Jose M. (1 October 2012).
"A survey of visual sensor network platforms"
.
Multimedia Tools and Applications
.
60
(3): 689?726.
doi
:
10.1007/s11042-011-0840-z
.
ISSN
1573-7721
.
S2CID
254837739
.
- ^
Williams, Adam; Ganesan, Deepak; Hanson, Allen (2007).
"Aging in place"
.
Proceedings of the 15th ACM international conference on Multimedia
. ACM Press. pp. 892?901.
doi
:
10.1145/1291233.1291435
.
ISBN
9781595937025
.
S2CID
16415553
.
- ^
Song, Bi; Soto, Cristian; Roy-Chowdhury, Amit K.; Farrell, Jay A. (September 2008).
"Decentralized camera network control using game theory"
.
2008 Second ACM/IEEE International Conference on Distributed Smart Cameras
. pp. 1?8.
doi
:
10.1109/ICDSC.2008.4635735
.
ISBN
978-1-4244-2664-5
.
S2CID
10467999
. Retrieved
15 May
2021
.
- ^
Obraczka, K.
; Manduchi, R.; Garcia-Luna-Aveces, J. J. (October 2002). "Managing the information flow in visual sensor networks".
The 5th International Symposium on Wireless Personal Multimedia Communications
(PDF)
. Vol. 3. pp. 1177?1181.
CiteSeerX
10.1.1.19.1917
.
doi
:
10.1109/WPMC.2002.1088364
.
ISBN
978-0-7803-7442-3
.
S2CID
1300523
.
- ^
Akdere, M.; Centintemel, U.; Crispell, D.; Jannotti, J.; Mao, J.; Taubin, G. (October 2006).
"Data-Centric Visual Sensor Networks for 3D Sensing"
(PDF)
.
Proc. 2nd Intl. Conf. On Geosensor Networks
.
- ^
Castanedo, F., Patricio, M. A., Garcia, J., and Molina, J. M. 2006. Extending surveillance systems capabilities using BDI cooperative sensor agents. In Proceedings of the 4th ACM international Workshop on Video Surveillance and Sensor Networks (Santa Barbara, California, USA, October 27 ? 27, 2006). VSSN '06. ACM Press, New York, NY, 131?138. DOI=
http://doi.acm.org/10.1145/1178782.1178802
External links
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