| Autor: |
Roxanne L. Canosa, Trevor R. H. Clarke |
| Rok vydání: |
2011 |
| Předmět: |
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| Zdroj: |
Real-Time Image and Video Processing |
| ISSN: |
0277-786X |
| DOI: |
10.1117/12.872355 |
| Popis: |
Wide area airborne surveillance (WAAS) systems are a new class of remote sensing imagers which have many military and civilian applications. These systems are characterized by long loiter times (extended imaging time over fixed target areas) and large footprint target areas. These characteristics complicate moving object detection and tracking due to the large image size and high number of moving objects. This research evaluates existing object detection and tracking algorithms withWAAS data and provides enhancements to the processing chain which decrease processing time and maintain or increase tracking accuracy. Decreases in processing time are needed to perform real-time or near real-time tracking either on the WAAS sensor platform or in ground station processing centers. Increased tracking accuracy benefits real-time users and forensic (off-line) users. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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