Adaptive video communication for an intelligent distributed system: Tuning sensors parameters for surveillance purposes

Machine Vision and Applications

Volumn 19, Issue 5-6, 2008, Pages 359-373

  Micheloni, Christian ^a   Lestuzzi, Marco ^a   Foresti, Gian Luca ^a  

^a UNIVERSITY OF UDINE   (Italy)

Author keywords

Multi sensors; Surveillance; Transmission

Indexed keywords

ADAPTIVE SYSTEMS; BANDWIDTH; IMAGE CODING; IMAGE COMMUNICATION SYSTEMS; INTELLIGENT SYSTEMS; NETWORK ARCHITECTURE; NETWORK PROTOCOLS; OBJECT RECOGNITION; SENSOR NETWORKS; SENSORS; WIRELESS NETWORKS;

AVAILABLE BANDWIDTH; DISTRIBUTED COMMUNICATIONS; DISTRIBUTED INTELLIGENCE; DISTRIBUTED SYSTEMS; EVENT ANALYSIS; FRAME RATES; HETEROGENEOUS CHANNELS; INFORMATION SHARING; IP-NETWORKS; MULTI SENSORS; MULTIPLE PROCESSING UNITS; OBJECT DETECTION; RESEARCH COMMUNITIES; SURVEILLANCE; SURVEILLANCE SYSTEMS; SYSTEM ARCHITECTURES; TRANSMISSION; VIDEO COMMUNICATIONS; VIDEO QUALITY; VIDEO SURVEILLANCE SYSTEM; VIDEO TRANSMISSIONS;

SECURITY SYSTEMS;

EID: 54849393000     PISSN: 09328092     EISSN: 14321769     Source Type: Journal    
DOI: 10.1007/s00138-007-0069-z     Document Type: Article

References (29)

1. Bhandarkar, S., Luo, X.: Fast and robust background updating for real-time traffic surveillance and monitoring. In: IEEE International Conference on Computer Vision and Pattern Recognition, vol. 3, pp. 55-59. San Diego (2005)
2. G. Bjontegaard K. Lillevold R. Danielsen 1996 A comparison of different coding formats for digital coding of video using mpeg-2 IEEE Trans Image Process 5 8 1271 1276
3. R. Collins A. Lipton H. Fujiyoshi T. Kanade 2001 Algorithms for cooperative multisensor surveillance Proc IEEE 89 1456 1477
4. Collins, R., Lipton, A., Kanade, T., Fujiyoshi, H., Tsin, D.D.Y., Tolliver, D., Enomoto, N., Hasegawa, O.: A system for video surveillance and monitoring. Technical Report CMU-RI-TR-00-12, Robotics Institute, Carnegie Mellon University, Pittsburgh (2000)
5. J. Fan D. Yau A. Elmagarmid W. Aref 2001 Automatic image segmentation by integrating color-edge extractionand seeded region growing IEEE Trans Image Process 10 10 1454 1466
6. G. Foresti T. Dolso 2004 Adaptive high-order neural trees for pattern recognitionadaptive high-order neural trees for pattern recognition IEEE Trans Syst Man Cybern Part B 34 2 988 996
7. G. Foresti C. Micheloni L. Snidaro P. Remagnino T. Ellis 2005 Advanced image and video processing in active video-based surveillancesystems IEEE Signal Process Mag 22 2 25 37
8. G. Foresti C. Regazzoni R. Visvanathan 2001 Scanning the issue technology-special issue on video communications,processing and understanding for third generation surveillance systems Proc IEEE 89 10 1355 1367
9. 4: Real-time surveillance of people and their activities IEEE Trans Pattern Anal Mach Intell 22 8 809 830
10. Hata, T., Kuwahara, N., Nozawa, T., Schwenke, D., Vetro,~A.: Surveillance system with object-aware video transcoder. In: International Workshop on Multimedia Signal Processing. Shangai, China (2005)
11. ISO/IEC: Coding of moving pictures and associated audio for digital storage media at up to about 1,5 Mbit/s - Part 2, 11172-2 edn (1993)
12. ISO/IEC JTC1: Coding f audio-Visual Objects -Part2: Visual, iso/iec 14 496-2 edn (1999))
13. ITU-T: Video Codec for Audiovisual Services at px 64 Kbit/s Version 1, itu-t reccomendation h.261 edn (1990)
14. Y.A. Ivanov A.F. Bobick 2000 Recognition of visual activities and interactions by stochastic parsing IEEE Trans Pattern Anal Mach Intell 22 8 852 872
15. J.N. Kapur P.K. Sahoo A.K.C. Wong 1985 A new method for gray-level picture thresholding using the entropy of the histogram Graph Models Image Process 29 273 285
16. S. Liao M. Pawlak 1996 On image analysis by moments IEEE Trans Pattern Anal Mach Intelli 18 254 266
17. D. Makris T. Ellis 2005 Learning semantic scene models from observing activity in visual surveillance IEEE Trans Syst Man Cybern Part B: Cybern 35 3 397 408
18. C. Micheloni G. Foresti L. Snidaro 2005 A network of cooperative cameras for visual-surveillance IEE Visual, Image Signal Process 152 2 205 212
19. N. Otsu 1979 A threshold selection method from gray level histograms IEEE Trans Syst Man Cybern SMC- 9 62 66
20. Petersen, J.: Understanding Surveillance Tehnologies. CRC, Boca Raton (2001)
21. Piciarelli, C., Foresti, G.: Event recognition by dynamic trajectory analysis and prediction. In: IEE Image for Crime Detection and Prevention. Savoy Place, London (2005)
22. T.W. Ridler S. Calvard 1978 Picture thresholding using an iterative selection method IEEE Trans Syst Man Cybern SMC- 8 630 632
23. Rosin, P.: Thresholding for change detection. In: Proceedings of IEEE International Conference on Computer Vision, pp.~274-279. Bombay, India (1998)
24. L. Snidaro G. Foresti 2003 Real-time thresholding with Euler numbers Pattern Recogn Lett 24 9-10 1533 1544
25. C. Stauffer W.E.L. Grimson 2000 Learning patterns of activity using real-time tracking IEEE Pattern Anal Mach Intell 22 8 747 757
26. G. Thimm E. Fiesler 1997 High-order and multilayer perceptron initialization IEEE Trans Neural Netw 8 2 349 359
27. T. Wiegand H. Scwarz A. Joch F. Kossentini G. Sullivan 2003 Rate-constrained coder control and comparison of video coding standard IEEE Trans Circuits Syst Video Technol 13 7 7
28. B. Zitova J. Flusser 2003 Image registration methods: a survey Image Vis Comput 21 977 1000
29. Z. Tao R. Nevatia 2004 Tracking multiple humans in complex situations IEEE Trans Pattern Anal Mach Intell 26 9 1208 1221