Details
| Original language | English |
|---|---|
| Publication status | Published - 27 Mar 2014 |
| Event | 7th International Conference on Distributed Smart Cameras, ICDSC 2013 - Palm Springs, United States Duration: 29 Oct 2013 → 1 Nov 2013 |
Conference
| Conference | 7th International Conference on Distributed Smart Cameras, ICDSC 2013 |
|---|---|
| Country/Territory | United States |
| City | Palm Springs |
| Period | 29 Oct 2013 → 1 Nov 2013 |
Abstract
This paper establishes a connection between object tracking from a systems point of view and the job-scheduling or job-shop problem. Often, surveillance areas cannot be fully monitored by a set of smart cameras at any given point in time. Decisions have to be made, which objects are to be tracked. The computer vision aspects of object tracking have made substantial strides which permits for elaborately planning the monitoring jobs. In this paper, object tracking is handled as a job-scheduling problem. As a result, tracked objects are considered as scheduling jobs that rely on smart cameras as resources that follow according tracking policies. The presented job-scheduling approach is based on proactive quotations advertised by the jobs. The main advantages of this algorithm are the avoidance of negotiation chains and the acceptance of local non-optimal solutions to benefit the overall performance.
ASJC Scopus subject areas
- Engineering(all)
- Electrical and Electronic Engineering
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2014. Paper presented at 7th International Conference on Distributed Smart Cameras, ICDSC 2013, Palm Springs, California, United States.
Research output: Contribution to conference › Paper › Research › peer review
}
TY - CONF
T1 - Object tracking as job-scheduling problem
AU - Jaenen, Uwe
AU - Spiegelberg, Henning
AU - Sommer, Lars
AU - Von Mammen, Sebastian
AU - Brehm, Juergen
AU - Haehner, Joerg
PY - 2014/3/27
Y1 - 2014/3/27
N2 - This paper establishes a connection between object tracking from a systems point of view and the job-scheduling or job-shop problem. Often, surveillance areas cannot be fully monitored by a set of smart cameras at any given point in time. Decisions have to be made, which objects are to be tracked. The computer vision aspects of object tracking have made substantial strides which permits for elaborately planning the monitoring jobs. In this paper, object tracking is handled as a job-scheduling problem. As a result, tracked objects are considered as scheduling jobs that rely on smart cameras as resources that follow according tracking policies. The presented job-scheduling approach is based on proactive quotations advertised by the jobs. The main advantages of this algorithm are the avoidance of negotiation chains and the acceptance of local non-optimal solutions to benefit the overall performance.
AB - This paper establishes a connection between object tracking from a systems point of view and the job-scheduling or job-shop problem. Often, surveillance areas cannot be fully monitored by a set of smart cameras at any given point in time. Decisions have to be made, which objects are to be tracked. The computer vision aspects of object tracking have made substantial strides which permits for elaborately planning the monitoring jobs. In this paper, object tracking is handled as a job-scheduling problem. As a result, tracked objects are considered as scheduling jobs that rely on smart cameras as resources that follow according tracking policies. The presented job-scheduling approach is based on proactive quotations advertised by the jobs. The main advantages of this algorithm are the avoidance of negotiation chains and the acceptance of local non-optimal solutions to benefit the overall performance.
UR - http://www.scopus.com/inward/record.url?scp=84899564037&partnerID=8YFLogxK
U2 - 10.1109/ICDSC.2013.6778211
DO - 10.1109/ICDSC.2013.6778211
M3 - Paper
AN - SCOPUS:84899564037
T2 - 7th International Conference on Distributed Smart Cameras, ICDSC 2013
Y2 - 29 October 2013 through 1 November 2013
ER -