Visual object tracking in a parking garage using compressed domain analysis

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 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.

Original document

The different versions of the original document can be found in:

• http://publica.fraunhofer.de/documents/N-520318.html

• http://dl.acm.org/ft_gateway.cfm?id=3208117&ftid=1982198&dwn=1,

http://dx.doi.org/10.1145/3204949.3208117 under the license http://www.acm.org/publications/policies/copyright_policy#Background

• https://dblp.uni-trier.de/db/conf/mmsys/mmsys2018.html#BeckerSSGHSR18,

https://dl.acm.org/citation.cfm?id=3208117,

https://doi.acm.org/10.1145/3204949.3208117,

https://academic.microsoft.com/#/detail/2811191079