Paper Info
Title
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.
Year
DOI
Venue
2018
10.1145/3204949.3208117
MMSys '18: 9th ACM Multimedia Systems Conference Amsterdam Netherlands June, 2018
Keywords
Field
DocType
Compressed-domain analysis, visual object tracking, indoor localization, infrastructure-based localization, driver-assistance systems, automatic driving
Domain analysis,Reference frame,Use case,Computer science,Advanced driver assistance systems,Robustness (computer science),Real-time computing,Video tracking,Unavailability,Management system
Conference
ISBN
Citations 
PageRank 
978-1-4503-5192-8
2
0.38
References 
Authors
13
7
Name
Order
Citations
PageRank
Daniel Becker1162.73
Matthias Schmidt220.71
Fernando Bombardelli da Silva320.71
Serhan Gül422.74
C. Hellge532832.26
Oliver Sawade6285.84
Ilja Radusch724437.15