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Visual object tracking in a parking garage using compressed domain analysis

: Becker, D.; Schmidt, M.; Da Silva, F.B.; Gül, S.; Hellge, C.; Sawade, O.; Radusch, I.


Association for Computing Machinery -ACM-:
9th ACM Multimedia Systems Conference, MMSys 2018. Proceedings : Amsterdam, The Netherlands, June 12-15, 2018
New York: ACM, 2018
ISBN: 978-1-4503-5192-8
Multimedia Systems Conference (MMSys) <9, 2018, Amsterdam>
Fraunhofer HHI ()

Modern driver assistance systems enable a variety of use cases which rely on accurate localization information of all traffic participants. Due to the unavailability of satellite-based localization, the use of infrastructure cameras is a promising alternative in indoor spaces such as parking garages. This paper presents a parking management system which extends the previous work of the eValet system with a low-complexity tracking functionality on compressed video bitstreams (compressed-domain tracking). The advantages of this approach include the improved robustness to partial occlusions as well as a resource-efficient processing of compressed video bit-streams. We have separated the tasks into different modules which are integrated into a comprehensive architecture. The demonstrator setup includes a 2D visualizer illustrating the operation of the algorithms on a single camera stream and a 3D visualizer displaying the abstract object detections in a global reference frame.