Abstract
Video surveillance technology is getting important today, in order to maintain the safety of pedestrians passing through public spaces. Tracking pedestrians across the camera network is important to understand each pedestrian’s behavior from the image sequence of a long period. For that purpose, we developed an occlusion robust tracking algorithm of pedestrians in the panning images by the combination between the S-T MRF model and pattern recognition methods of Snakes and HOG classifier. Tracking in panning images would extend the field of view of single camera. In addition, we developed an algorithm to match pedestrians between cameras which have overlapping area with each other in their field of view. Finally, the tracking algorithm in panning images and the pedestrian matching algorithm between the overlapping images were combined to extend the area of pedestrian surveillance.
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Haritaoglu, I., Harwood, D., Davis, L.S.: “W4: real-time surveillance of people and theiractivities”. PAMI, IEEE Trans 22(8), 809–830 (2000)
Y. Iwashita, R. Kurazume, T. Tsuji, K. Hara,T. Hasegawa, “Fast Implementation of Level Set Method and Its Realtime Applications,” IEEE International Conference on Systems, Man and Cybernetics 2004 (SMC'04)
S.Kamijo, Y.Matsushita, K.Ikeuchi, M.Sakauchi, “Occlusion Robust Vehicle Tracking utilizing Spatio-Temporal Markov Random Field Model”, 7thWorld Congress on ITS, Torino, Nov. 2000.
S.Kamijo, K.Ikeuchi, M.Sakauchi, “Vehicle Tracking in Low-angle and Front-View Images based on Spatio-Temporal Markov Random Field Model” 8th World Congress on ITS, Sydney Oct.2001, CD-ROM.
D. Comaniciu, V Ramesh, P Meer, “Real-time tracking of non-rigid objects using mean shift,” IEEE Computer Society Conference on CVPR, 2000
D. Comaniciu, V Ramesh, P Meer, “ Kernel based object Tracking,” PAMI, IEEE Trans, Vol.25 No.5, May 2003, pp.564–577
Darrell, T., Gordon, G., Harville, M., Woodfill, J.: Integrated person tracking using stereo, color, and pettern detection. Int’l J, Computer Vision 37(2), 175–185 (June 2000)
Sohaib Khan, Mubarak Shah, “Consistent Labeling of Tracked Objects in Multiple Cameras with Overlapping Fields of View,” PAMI, IEEE Trans., Vol25 No.10, Oct 2003
Q. Cai and J.K. Aggarwal, “Tracking Human Motion in Structured Environments Using a Distributed Camera System,” IEEE Trans. PAMI, vol.21 no.11, Nov. 1999, pp.1241–1247.
N Paragios, R Deriche, “Geodesic active contours and level sets for the detection and tracking of moving objects,” PAMI, IEEE Transactions on, Vol.22 No.3, March 2000, pp.266–280
M. Niethammer and A. Tannenbaum, “Dynamic level sets for visual tracking,” Proceedings of the Conference on Decision and Control, IEEE, Vol.5, Dec2003, pp4883–4888
S.Kamijo, M.Sakauchi, “Simultaneous Tracking of Pedestrians and Vehicles in Cluttered Images at Intersections,” 10th World Congress on ITS, Madrid, November.2003, CD-ROM
M. Kass, A. Witikin, D. Terzopoulos, “Snakes: Active Contour Models,” Proc. of 1st ICCV, pp.259–268, 1987
Sakaguchi and Okayama, “Snakes with area term,” Spring Confernce of IEICE Japan, D-555, 1991
N. Dalal and B. Triggs, “Histograms of Oriented Gradients for Human Detection”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2005.
M. Bertozzi, A. Broggi, M. DelRose, M. Felisa, A. Rakotomamonjy, F.Suard, “A Pedestrian Detector Using Histograms of Oriented Gradients and a Support Vector Machine Classifier”, Intelligent Transportation Systems Conference (ITSC), IEEE, 2007
C. Wang, J. Lien, “AdaBoost Learning for Human Detection Based on Histograms of Oriented Gradients”, ACCV 2007, Part I, LNCS 4843, pp.885–895, Springer, Heidelberg, 2007
P. Viola, M. Jones, D. Snow, “Detecting Pedestrians Using Patterns of Motion and Appearance”, International Journal of Computer Vision (IJCV), pp.153.161 , 2005
M. Oren, C. Papageorgiou, P. Sinha, E. Osuna, and T. Poggio, “Pedestrian Detection Using Wavelet Templates,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 193–199, 1997.
Haga, T., Sumi, K., Yagi, Y.: Human Tracking Using the Temporal Averaging Silhouette with an Active Camera. IEICE J88-D-II(2), 291–301 (2005)
S.Kamijo,M.Sakauchi, "Simultaneous Tracking of Pedestrians and Vehicles in Cluttered Images at Intersections", 10th World Congress on ITS,CD-ROM, 2003–11
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This research was supported by the National Institute of Information and Communications Technologies (NICT) of Japan.
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Hyodo, Y., Fujimura, K., Naito, T. et al. Pedestrian Tracking Across Panning Camera Network. Int. J. ITS Res. 8, 10–25 (2010). https://doi.org/10.1007/s13177-009-0001-1
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DOI: https://doi.org/10.1007/s13177-009-0001-1