Quality-based fusion of multiple video sensors for video surveillance

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 37, Issue 4, 2007, Pages 1044-1051

  Snidaro, Lauro ^a   Niu, Ruixin ^b   Foresti, Gian Luca ^a   Varshney, Pramond K ^b  

^a UNIVERSITY OF UDINE   (Italy)

^b Syracuse University   (United States)

Author keywords

Data fusion; Object tracking; Segmentation quality; Video surveillance

Indexed keywords

DATA FUSION; IMAGE QUALITY; IMAGE SEGMENTATION; OBJECT RECOGNITION;

OBJECT TRACKING; SEGMENTATION QUALITY; VIDEO SENSORS; VIDEO SEQUENCES; VIDEO SURVEILLANCE;

IMAGE SENSORS;

ALGORITHM; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; IMAGE SUBTRACTION; LETTER; METHODOLOGY; ORGANIZATION AND MANAGEMENT; VIDEORECORDING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; IMAGE INTERPRETATION, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; SECURITY MEASURES; SUBTRACTION TECHNIQUE; VIDEO RECORDING;

EID: 34547127391     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2007.895331     Document Type: Article

References (15)

1. G. L. Foresti, C. Micheloni, L. Snidaro, P. Remagnino, and T. Ellis, "Active video-based surveillance systems," IEEE Signal Process. Mag., vol. 22, no. 2, pp. 25-37, Mar. 2005.
2. G. L. Foresti, C. S. Regazzoni, and P. K. Varshney, Multisensor Surveillance Systems: The Fusion Perspective. Norwell, MA: Kluwer, 2003.
3. D. Makris and T. Ellis, "Learning semantic scene models from observing activity in visual surveillance," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 35, no. 3, pp. 397-408, Jun. 2005.
4. Y. Bar-Shalom, X. R. Li, and T. Kirubarajan, Estimation With Applications to Tracking and Navigation. New York: Wiley-Interscience, Jun. 2001.
5. D. L. Hall and S. A. McMullen, Mathematical Techniques in Multisensor Data Fusion. Norwood, MA: Artech House, Mar. 2004.
6. J. Triesch and C. von der Malsburg, "Democratic integration: Self-organized integration of adaptive cues," Neural Comput., vol. 13, no. 9, pp. 2049-2074, 2001.
7. O. Kahler, J. Denzler, and J. Triesch, "Hierarchical sensor data fusion by probabilistic cue integration for robust 3D object tracking," in Proc. 6th IEEE Southwest Symp. Image Anal. and Interpret., Lake Tahoe, NV, Mar. 2004, pp. 216-220.
8. L. Snidaro, G. L. Foresti, R. Niu, and P. K. Varshney, "Sensor fusion for video surveillance," in Proc. 7th Int. Conf. Inf. Fusion. Stockholm, Sweden: Int. Soc. Inf. Fusion, Jun. 2004, vol. 2, pp. 739-746.
9. I. Avcibaş, B. Sankur, and K. Sayood, "Statistical evaluation of image quality measures," J. Electron. Imaging, vol. 11, no. 2, pp. 206-223, 2002.
10. Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, "Image quality assessment: From error visibility to structural similarity," IEEE Trans. Image Process., vol. 13, no. 4, pp. 600-612, Apr. 2004.
11. P. L. Correia and F. Pereira, "Objective evaluation of video segmentation quality," IEEE Trans. Image Process., vol. 12, no. 2, pp. 186-200, Feb. 2003.
12. R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, 2nd ed. New York: Cambridge Univ. Press, Mar. 2004.
13. Y. Bar-Shalom and X. R. Li, Multitarget-Multisensor Tracking: Principles and Techniques. Storrs, CT: YBS Publishing, 1995.
14. J. B. Gao and C. J. Harris, "Some remarks on Kalman filters for the multisensor fusion," Inf. Fusion, vol. 3, no. 3, pp. 191-201, Sep. 2002.
15. H. Chen, T. Kirubarajan, and Y. Bar-Shalom, "Performance limits of track-to-track fusion versus centralized estimation: Theory and application," IEEE Trans. Aerosp. Electron. Syst., vol. 39, no. 2, pp. 386-400, Apr. 2003.