提出形状感知的OBB转HBB方法，提升遥感船舶检测精度
Shape-Aware Oriented Bounding Box (OBB) to Horizontal Bounding Box (HBB) Conversion
- 结合船体形状、饱满度与方向，生成更紧致的轴对齐框
- 相比基线方法减少3.2%空域冗余，保留更多有效检测信息
- 适用于高分辨率遥感图像中的船舶等有向目标检测
航空与卫星影像中的精确目标检测依赖于边界框表示方式。对于船只、飞机等具有空间朝向性的物体，定向边界框（OBB）相比水平边界框（HBB）具有更紧密的拟合效果和更强的非极大值抑制能力。然而，现有从OBB到HBB的后处理转换方法要么引入过多空白背景区域，要么丢失部分检测数据。本文提出一种针对遥感图像中船舶检测的形状感知型OBB转HBB新方法，融合船体轮廓形状、整体饱满度及边界框朝向信息，生成更紧凑的轴对齐边界框表示。在三种基准方法（最小最大外接矩形、面积等效矩形、GBB边缘化矩形）上进行对比评估，结果表明该方法显著降低冗余空间并保留关键检测内容。
原文摘要 · Abstract (English)
Accurate object detection in aerial and satellite imagery is dependent upon the bounding box representation. This is especially true for spatially oriented objects such as ships or aircrafts. Oriented Bounding Boxes (OBB) have a tighter fit and more robust non-max suppression compared to Horizontal Bounding Boxes (HBB), any current post-processing conversion from OBB to HBB either introduces excess empty and background space or removes data from the detection. This paper introduces a novel approach for a shape-aware OBB-to-HBB conversion for ship detection in remote sensing imagery. It leverages hull shape, hull fullness, and the bounding box orientation to produce a tighter axis-aligned HBB representation. The proposed method is benchmarked against three baselines methods for OBBto-HBB conversion, Outer HBB which uses minimum and maximum, Area Equivalent HBB and GBB Marginalized HBB.
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。