Abstract
Surveillance systems have long been in the focus of the research community. Although the accurate detection of the human presence in the scene is now possible even under extreme environmental conditions via the advanced modern camera sensors, efficient personalized tracking is still an open issue and a significant challenge for researchers addressing. Moreover, personalized tracking will not only enhance the tracking robustness but it can also find useful application in several commercial surveillance use-cases, ranging from security to occupancy statistics (i.e. per building, per space and per human). In this respect, this paper introduces a novel the biometric approach for enhanced privacy preserving human tracking based on a novel soft-biometric feature of humans. The moving blobs in the recorded scene can be easily detected in the colour images, while the human silhouettes are detected from the corresponding depth ones. The state-of-the-art 3D Weighted Walkthroughs (3DWW) transformation is applied on the extracted human 3D point cloud, forming thus, a short-term soft biometric signature. The re-authentication of the humans is performed via the comparison of their last valid signature with current one. A thorough analysis on the adjustment of the system’s optimal operational settings has been carried out and the experimental results illustrate the promising robustness, accuracy and efficiency on human tracking performance.
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Acknowledgment
This work is co-funded by the European Union (EU) within the SMILE project under grant agreement number 740931. The SMILE project is part of the EU Framework Program for Research and Innovation Horizon 2020.
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Stavropoulos, G., Dimitriou, N., Drosou, A., Tzovaras, D. (2019). A Short-Term Biometric Based System for Accurate Personalized Tracking. In: Tzovaras, D., Giakoumis, D., Vincze, M., Argyros, A. (eds) Computer Vision Systems. ICVS 2019. Lecture Notes in Computer Science(), vol 11754. Springer, Cham. https://doi.org/10.1007/978-3-030-34995-0_50
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DOI: https://doi.org/10.1007/978-3-030-34995-0_50
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