Computer Science – Artificial Intelligence
Scientific paper
2004-11-19
Proc SPIE Vol 5429, p 162-171 (2004)
Computer Science
Artificial Intelligence
10 pages
Scientific paper
10.1117/12.542027
We describe the recently introduced extremal optimization algorithm and apply it to target detection and association problems arising in pre-processing for multi-target tracking. Here we consider the problem of pre-processing for multiple target tracking when the number of sensor reports received is very large and arrives in large bursts. In this case, it is sometimes necessary to pre-process reports before sending them to tracking modules in the fusion system. The pre-processing step associates reports to known tracks (or initializes new tracks for reports on objects that have not been seen before). It could also be used as a pre-process step before clustering, e.g., in order to test how many clusters to use. The pre-processing is done by solving an approximate version of the original problem. In this approximation, not all pair-wise conflicts are calculated. The approximation relies on knowing how many such pair-wise conflicts that are necessary to compute. To determine this, results on phase-transitions occurring when coloring (or clustering) large random instances of a particular graph ensemble are used.
No associations
LandOfFree
Extremal optimization for sensor report pre-processing does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Extremal optimization for sensor report pre-processing, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Extremal optimization for sensor report pre-processing will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-85242