Visual object tracking in a parking garage using compressed domain analysis

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Abstract

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 bitstreams. 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.

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APA

Becker, D., Schmidt, M., Da Silva, F. B., Gül, S., Hellge, C., Sawade, O., & Radusch, I. (2018). Visual object tracking in a parking garage using compressed domain analysis. In Proceedings of the 9th ACM Multimedia Systems Conference, MMSys 2018 (pp. 513–516). Association for Computing Machinery, Inc. https://doi.org/10.1145/3204949.3208117

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