© The Institution of Engineering and Technology
Pan–tilt–zoom (PTZ) cameras play an important role in visual surveillance system. Dual-PTZ camera system is the simplest and most typical one. The superiority of this system lies in that it can obtain both large-view information and high-resolution local-view information of the tracked object at the same time. One method to achieve such task is to use master–slave configuration. One camera (master) tracks moving objects at low resolution and provides the positional information to another camera (slave). Then the slave camera can point towards the object at high resolution and track it dynamically. In this paper, we propose a novel framework exploiting planar ground assumption to achieve cooperative tracking. The approach differs from conventional methods in that we exploit planar geometric constraint to solve the camera collaboration problem. Compared with the existing approach, the proposed framework can be used in the case of wide baseline, and allows the depth change of the tracked object. The proposed method can also adapt to the dynamic change of the surveillance scene. Besides, we also describe a self-calibration method of homography matrix which is induced by the ground plane between two cameras. We demonstrate the effectiveness of the proposed method by testing it with a tracking system for surveillance applications.
References
-
-
1)
-
18. Park, U., Choi, H.C., Jain, A.K., Lee, S.: ‘Face tracking and recognition at a distance: a coaxial & concentric PTZ camera system’, IEEE Trans. Inf. Forensics Sec., 2013, 8, (10), pp. 1665–1677 (doi: 10.1109/TIFS.2013.2261061).
-
2)
-
12. Micheloni, C., Foresti, G.L.: ‘Real time image processing for active monitoring of wide areas’, J. Visual Commun. Image Represent., 2006, 17, (3), pp. 589–604 (doi: 10.1016/j.jvcir.2005.08.002).
-
3)
-
15. Tarhan, M., Altug, E.: ‘A catadioptric and pan–tilt–zoom camera pair object tracking system for UAVS’, J. Intell. Rob. Syst., 2011, 61, (1), pp. 119–134 (doi: 10.1007/s10846-010-9504-x).
-
4)
-
28. Stauffer, C., Grimson, W.E.L.: ‘Adaptive background mixture models for real-time tracking’. IEEE Int. Conf. Computer Vision and Pattern Recognition, 1999, pp. 246–252.
-
5)
-
17. Zhou, X.H., Collins, R.T., Kanade, T., Metes, P.: ‘A master–slave system to acquire biometric imagery of humans at a distance’. ACM SIGMM Int. Workshop on Video Surveillance, 2003, pp. 113–120.
-
6)
-
11. Suhr, J.K., Jung, H.G., Li, G., Noh, S.I., Kim, J.: ‘Background compensation for pan-tilt-zoom cameras using 1-D feature matching and outlier rejection’, IEEE Trans. Circuits Syst. Video Technol., 2011, 21, (3), pp. 371–377 (doi: 10.1109/TCSVT.2010.2087811).
-
7)
-
19. Horaud, R., Knossow, D., Michaelis, M.: ‘Camera cooperation for achieving visual attention’, Mach. Vis. Appl., 2006, 16, (6), pp. 331–342 (doi: 10.1007/s00138-005-0182-9).
-
8)
-
9. Varcheie, P.D.Z., Bilodeau, G.A.: ‘People tracking using a network-based PTZ camera’, Mach. Vis. Appl., 2011, 22, (4), pp. 671–690 (doi: 10.1007/s00138-010-0300-1).
-
9)
-
25. Zhang, Z., Li, M., Huang, K., Tan, T.: ‘Practical camera auto-calibration based on object appearance and motion for traffic scene surveillance’. IEEE Int. Conf. Computer Vision, 2008, pp. 1–8.
-
10)
-
16. Chen, C., Yao, Y., Page, D., Abidi, B., Koschan, A., Abidi, M.: ‘Heterogeneous fusion of omnidirectional and PTZ cameras for multiple object tracking’, IEEE Trans. Circuits Syst. Video Technol., 2008, 18, (8), pp. 1052–1063 (doi: 10.1109/TCSVT.2008.928223).
-
11)
-
10. Haj, M.A., Bagdanov, A.D., Gonzalez, J., Roca, F.X.: ‘Reactive object tracking with a single PTZ camera’. Int. Conf. Pattern Recognition, 2010, pp. 1690–1693.
-
12)
-
13. Kim, S.W., Yun, K., Yi, K.M., Kim, S.J., Choi, J.Y.: ‘Detection of moving objects with a moving camera using non-panoramic background model’, Mach. Vis. Appl., 2013, 24, (5), pp. 1015–1028 (doi: 10.1007/s00138-012-0448-y).
-
13)
-
1. Ahmad, I., He, Z., Liao, M., Pereira, F., Sun, M.T.: ‘Special issue on video surveillance’, IEEE Trans. Circuits Syst. Video Technol., 2008, 18, (8), pp. 1001–1005 (doi: 10.1109/TCSVT.2008.929646).
-
14)
-
8. Xue, K., Liu, Y., Ogunmakin, G., Chen, J., Zhang, J.: ‘Panoramic Gaussian mixture model and large-scale range background subtraction method for PTZ camera-based surveillance systems’, Mach. Vis. Appl., 2012, 11, (4), pp. 1–16.
-
15)
-
7. Bernardin, K., Camp, F.V.D., Stiefelhagen, R.: ‘Automatic person detection and tracking using fuzzy controlled active cameras’. IEEE Int. Conf. Computer Vision and Pattern Recognition, 2007, pp. 1–8.
-
16)
-
35. Sony Corporation: ‘Sony EVI-D70/D70P Technical Manual’, 2003.
-
17)
-
27. Hodlmoser, M., Micusik, B., Kampel, M.: ‘Camera auto-calibration using pedestrians and zebra-crossing’. IEEE Int. Conf. Computer Vision Workshops, 2011, pp. 1697–1704.
-
18)
-
22. Li, Y., Song, L., Wang, J.: ‘Automatic weak calibration of master–slave surveillance system based on mosaic image’. Int. Conf. Pattern Recognition, 2010, pp. 1824–1827.
-
19)
-
3. Radke, R.J., Andra, S., Al-Kofahi, O., Roysam, B.: ‘Image change detection algorithms: a systematic survey’, IEEE Trans. Image Process., 2005, 14, (3), pp. 294–307.
-
20)
-
21. Lu, Y., Payandeh, S.: ‘Cooperative hybrid multi-camera tracking for people surveillance’, Can. J. Electr. Comput. Eng., 2008, 33, (3), pp. 145–152 (doi: 10.1109/CJECE.2008.4721631).
-
21)
-
4. Salti, S., Cavallaro, A., Stefano, L.D.: ‘Adaptive appearance modeling for video tracking: survey and evaluation’, IEEE Trans. Image Process., 2012, 21, (10), pp. 4334–4348.
-
22)
-
I. Haritaoglu ,
D. Hartwood ,
L.S. Davis
.
Real-time surveillance of people and their activities.
IEEE Trans. Pattern Anal. Mach. Intell.
,
809 -
830
-
23)
-
14. Wang, X.: ‘Intelligent multi-camera video surveillance: a review’, Pattern Recognit. Lett., 2013, 34, (1), pp. 3–19 (doi: 10.1016/j.patrec.2012.07.005).
-
24)
-
26. Micusik, B., Pajdla, T.: ‘Simultaneous surveillance camera calibration and foot-head homology estimation from human detections’. IEEE Int. Conf. Computer Vision, 2010, pp. 1562–1569.
-
25)
-
M.A. Fischler ,
R.C. Bolles
.
Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography.
Commun. ACM
,
381 -
395
-
26)
-
5. Jiang, F., Yuan, J., Tsaftaris, S., Katsaggelos, A.: ‘Anomalous video event detection using spatiotemporal context’, Comput. Vis. Image Underst., 2011, 115, (3), pp. 323–333 (doi: 10.1016/j.cviu.2010.10.008).
-
27)
-
30. Hartley, R.I.: ‘In defense of the eight-point algorithm’, IEEE Trans. Pattern Anal. Mach. Intell., 1997, 19, (6), pp. 580–593 (doi: 10.1109/34.601246).
-
28)
-
D.G. Lowe
.
Distinctive image features from scale-invariant keypoints.
Int. J. Comput. Vis
,
2 ,
91 -
110
-
29)
-
23. Bimbo, A.D., Dini, F., Lisanti, G., Pernici, F.: ‘Exploiting distinctive visual landmark maps in pan-tilt-zoom camera networks’, Comput. Vis. Image Underst., 2010, 114, (6), pp. 611–623 (doi: 10.1016/j.cviu.2010.01.007).
-
30)
-
17. Lv, F., Zhao, T., Nevatia, R.: ‘Camera calibration from video of a walking human’, IEEE Trans. Pattern Anal. Mach. Intell., 2006, 28, (9), pp. 1513–1518 (doi: 10.1109/TPAMI.2006.178).
-
31)
-
20. Jain, A., Kopell, D., Kakligian, K., Wang, Y.F.: ‘Using stationary-dynamic camera assemblies for wide-area video surveillance and selective attention’. IEEE Int. Conf. Computer Vision and Pattern Recognition, 2006, pp. 537–544.
-
32)
-
31. Yang, Y., Levine, M.: ‘The background primal sketch: an approach for tracking moving objects’, Mach. Vis. Appl., 1992, 5, (1), pp. 17–34 (doi: 10.1007/BF01213527).
-
33)
-
2. Kim, I.S., Choi, H.S., Yi, K.M., Choi, J.Y., Kong, S.G.: ‘Intelligent visual surveillance-a survey’, Int. J. Control Autom. Syst., 2010, 8, (5), pp. 926–939 (doi: 10.1007/s12555-010-0501-4).
-
34)
-
6. Mstsuyama, T., Ukita, N.: ‘Real-time multitarget tracking by a cooperative distributed vision system’, Proc. IEEE, 2002, vol. 90, (7), pp. 1136–1150.
-
35)
-
33. Levenberg, K.: ‘A method for the solution of certain nonlinear problems in least squares’, Q. Appl. Math., 1994, 2, (2), pp. 164–168.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cvi.2013.0246
Related content
content/journals/10.1049/iet-cvi.2013.0246
pub_keyword,iet_inspecKeyword,pub_concept
6
6