79:. 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
357:
Castanedo, F., Patricio, M. A., García, 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).
83:
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,
44:(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.
55:, 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
32:
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. A visual sensor network may be a type of
47:
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
36:, 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
40:, communication and storage capabilities, and possibly one or more central computers, where image data from multiple cameras is further processed and
446:
312:
246:
201:
451:
84:
where the network would automatically select the "best" view (perhaps even an arbitrarily generated one) of a live event.
280:; Manduchi, R.; Garcia-Luna-Aveces, J. J. (October 2002). "Managing the information flow in visual sensor networks".
59:. In light of this, communication in visual sensor networks differs substantially from traditional sensor networks.
386:
76:
413:
Feature-Based Image
Comparison for Semantic Neighbor Selection in Resource-Constrained Visual Sensor Networks
93:
72:
33:
290:
295:
318:
252:
207:
162:
80:
412:
426:
308:
242:
197:
154:
134:
336:
Akdere, M.; Centintemel, U.; Crispell, D.; Jannotti, J.; Mao, J.; Taubin, G. (October 2006).
281:
396:
300:
234:
189:
146:
37:
377:
98:
133:
Tavli, Bulent; Bicakci, Kemal; Zilan, Ruken; Barcelo-Ordinas, Jose M. (1 October 2012).
277:
440:
390:
181:
166:
113:
52:
41:
256:
225:
Song, Bi; Soto, Cristian; Roy-Chowdhury, Amit K.; Farrell, Jay A. (September 2008).
211:
322:
108:
68:
29:
337:
238:
226:
408:
373:
304:
283:
The 5th
International Symposium on Wireless Personal Multimedia Communications
150:
359:
158:
378:
Coverage
Estimation in the Presence of Occlusions for Visual Sensor Networks
193:
103:
400:
231:
2008 Second ACM/IEEE International
Conference on Distributed Smart Cameras
395:, Advances in Multimedia, vol. 2009, Article ID 640386, 21 pages, 2009.
67:
Visual sensor networks are most useful in applications involving area
48:
415:. EURASIP Journal on Image and Video Processing, Volume 2010 (2010).
186:
Proceedings of the 15th ACM international conference on
Multimedia
431:
227:"Decentralized camera network control using game theory"
180:
Williams, Adam; Ganesan, Deepak; Hanson, Allen (2007).
338:"Data-Centric Visual Sensor Networks for 3D Sensing"
358:VSSN '06. ACM Press, New York, NY, 131–138. DOI=
427:Virtual Vision for Smart Camera Sensor Networks
135:"A survey of visual sensor network platforms"
8:
345:Proc. 2nd Intl. Conf. On Geosensor Networks
360:http://doi.acm.org/10.1145/1178782.1178802
294:
125:
28:is a network of spatially distributed
7:
289:. Vol. 3. pp. 1177–1181.
51:, cameras are directional in their
392:A Survey of Visual Sensor Networks
14:
139:Multimedia Tools and Applications
447:Applications of computer vision
188:. ACM Press. pp. 892–901.
1:
468:
239:10.1109/ICDSC.2008.4635735
26:intelligent camera network
305:10.1109/WPMC.2002.1088364
151:10.1007/s11042-011-0840-z
77:environmental monitoring
452:Wireless sensor network
406:
384:
371:
194:10.1145/1291233.1291435
94:Wireless sensor network
34:wireless sensor network
380:. DCOSS 2008: 346–356
18:visual sensor network
22:smart camera network
401:10.1155/2009/640386
81:object recognition
314:978-0-7803-7442-3
248:978-1-4244-2664-5
459:
362:
355:
349:
348:
342:
333:
327:
326:
298:
288:
274:
268:
267:
265:
263:
233:. pp. 1–8.
222:
216:
215:
182:"Aging in place"
177:
171:
170:
130:
38:image processing
467:
466:
462:
461:
460:
458:
457:
456:
437:
436:
423:
418:
366:
365:
356:
352:
340:
335:
334:
330:
315:
286:
276:
275:
271:
261:
259:
249:
224:
223:
219:
204:
179:
178:
174:
132:
131:
127:
122:
99:Computer vision
90:
65:
12:
11:
5:
465:
463:
455:
454:
449:
439:
438:
435:
434:
429:
422:
421:External links
419:
417:
416:
405:
403:
383:
381:
372:^ Cheng Qian,
370:
367:
364:
363:
350:
328:
313:
296:10.1.1.19.1917
269:
247:
217:
202:
172:
145:(3): 689–726.
124:
123:
121:
118:
117:
116:
111:
106:
101:
96:
89:
86:
64:
61:
13:
10:
9:
6:
4:
3:
2:
464:
453:
450:
448:
445:
444:
442:
433:
430:
428:
425:
424:
420:
414:
410:
404:
402:
398:
394:
393:
388:
387:Heinzelman W.
382:
379:
375:
369:
368:
361:
354:
351:
346:
339:
332:
329:
324:
320:
316:
310:
306:
302:
297:
292:
285:
284:
279:
273:
270:
258:
254:
250:
244:
240:
236:
232:
228:
221:
218:
213:
209:
205:
203:9781595937025
199:
195:
191:
187:
183:
176:
173:
168:
164:
160:
156:
152:
148:
144:
140:
136:
129:
126:
119:
115:
114:Sensor fusion
112:
110:
107:
105:
102:
100:
97:
95:
92:
91:
87:
85:
82:
78:
74:
70:
62:
60:
58:
54:
53:field of view
50:
45:
43:
39:
35:
31:
27:
23:
19:
407:^ Yang Bai,
391:
353:
344:
331:
282:
278:Obraczka, K.
272:
260:. Retrieved
230:
220:
185:
175:
142:
138:
128:
109:Smart camera
69:surveillance
66:
63:Applications
56:
46:
30:smart camera
25:
21:
17:
15:
385:^ Soro S.,
441:Categories
409:Hairong Qi
374:Hairong Qi
120:References
291:CiteSeerX
167:254837739
159:1573-7721
104:Smartdust
257:10467999
212:16415553
88:See also
73:tracking
57:patterns
432:CMUcam3
323:1300523
49:sensors
321:
311:
293:
262:15 May
255:
245:
210:
200:
165:
157:
75:, and
341:(PDF)
319:S2CID
287:(PDF)
253:S2CID
208:S2CID
163:S2CID
42:fused
309:ISBN
264:2021
243:ISBN
198:ISBN
155:ISSN
397:doi
301:doi
235:doi
190:doi
147:doi
24:or
20:or
443::
411::
389::
376::
343:.
317:.
307:.
299:.
251:.
241:.
229:.
206:.
196:.
184:.
161:.
153:.
143:60
141:.
137:.
71:,
16:A
399::
347:.
325:.
303::
266:.
237::
214:.
192::
169:.
149::
Text is available under the Creative Commons Attribution-ShareAlike License. Additional terms may apply.