Name
Abstract | ||
|---|---|---|
In this paper, a real time method for detecting and tracking multiple dim targets in deep space background is presented. We matched the stars in tow continuous images to get their speed at first and found moving targets through speed in both images. Using the targets in the common frame data association is achieved. The Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter is used to track targets to solve the problem of targets disappearance. To initialize of the birth random finite sets (RFSs) the targets sequences are built to find new targets. Extensive experiments on real images sequences show that the proposed approach could effectively meet the requirements of the real-time detection with a low false alarm rate and a high detection probability. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-31919-8_37 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Keywords | Field | DocType |
GM-PHD filter,common frame data association,real time method,sequences show,high detection probability,birth random finite set,real image,Gaussian Mixture Probability Hypothesis,targets disappearance,targets sequence,real-time detection,dim target tracking base | Computer vision,Probability hypothesis density filter,Finite set,Stars,Data association,Gaussian,Artificial intelligence,Constant false alarm rate,Real image,NASA Deep Space Network,Mathematics | Conference |
Volume | Issue | ISSN |
7202 LNCS | null | 16113349 |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lei Li | 1 | 0 | 0.34 |
| Jinqiu Sun | 2 | 33 | 8.27 |
| Yu Zhu | 3 | 88 | 12.65 |
| Haisen Li | 4 | 4 | 3.24 |