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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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Acknowledgments

This research was supported by the National Institute of Information and Communications Technologies (NICT) of Japan.

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Correspondence to Yasuhide Hyodo.

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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

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