提出红外图像中目标检测识别跟踪算法的完整评估方法
METRIC: a complete methodology for performances evaluation of automatic target Detection, Recognition and Tracking algorithms in infrared imagery
- 构建面向检测/识别/跟踪任务的客观数据集与适配指标
- 在法国2ACI项目中验证了多类算法性能表现
- 适合红外视觉算法评测研究人员参考
本文针对红外图像中自动目标检测、识别与跟踪（ATD/R/T）算法的性能评估问题，提出一套完整的评估方法，涵盖客观图像数据集的构建与各类任务（检测、识别、跟踪）适配的评价指标定义。相关性能评估结果正在法国国防部资助的2ACI（自动目标成像获取）项目中进行分析与验证。
原文摘要 · Abstract (English)
In this communication, we deal with the question of automatic target detection, recognition and tracking (ATD/R/T) algorithms performance assessment. We propose a complete methodology of evaluation which approaches objective image datasets development and adapted metrics definition for the different tasks (detection, recognition and tracking). We present some performance results which are currently processed in a French-MoD program called 2ACI (``Acquisition Automatique de Cibles par Imagerie``).
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。