Abstract
The growing concerns about persons security and the increasing popularity of pan-tilt-zoom (PTZ) cameras, have been raising the interest on automated master-slave surveillance systems. Such systems are typically composed by (1) a fixed wide-angle camera that covers a large area, detects and tracks moving objects in the scene; and (2) a PTZ camera, that provides a close-up view of an object of interest. Previously published approaches attempted to establish 2D correspondences between the video streams of both cameras, which is a ill-posed formulation due to the absence of depth information. On the other side, 3D-based approaches are more accurate but require more than one fixed camera to estimate depth information. In this paper, we describe a novel method for easy and precise calibration of a master-slave surveillance system, composed by a single fixed wide-angle camera. Our method exploits single view metrology to infer 3D data of the tracked humans and to self-perform the transformation between camera views. Experimental results in both simulated and realistic scenes point for the effectiveness of the proposed model in comparison with the state-of-the-art.
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Acknowledgements
This work is supported by ‘FCT - Fundação para a Ciência e Tecnologia’ (Portugal) through the research grant ‘SFRH/BD/92520/2013’, and the funding from ‘FEDER - QREN - Type 4.1 - Formação Avançada’, co-founded by the European Social Fund and by national funds through Portuguese ‘MEC - Ministério da Educação e Ciência’. It is also supported by the IT - Instituto de Telecomunicações through ‘PEst-OE/EEI/LA0008/2013’.
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Neves, J.C., Moreno, J.C., Barra, S., Proença, H. (2015). A Calibration Algorithm for Multi-camera Visual Surveillance Systems Based on Single-View Metrology. In: Paredes, R., Cardoso, J., Pardo, X. (eds) Pattern Recognition and Image Analysis. IbPRIA 2015. Lecture Notes in Computer Science(), vol 9117. Springer, Cham. https://doi.org/10.1007/978-3-319-19390-8_62
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DOI: https://doi.org/10.1007/978-3-319-19390-8_62
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