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Object count/area graphs for the evaluation of object detection and segmentation algorithms

机译:对象计数/面积图,用于评估对象检测和分割算法

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摘要

Evaluation of object detection algorithms is a non-trivial task: a detection result is usually evaluated by comparing the bounding box of the detected object with the bounding box of the ground truth object. The commonly used precision and recall measures are computed from the overlap area of these two rectangles. However, these measures have several drawbacks: they don't give intuitive information about the proportion of the correctly detected objects and the number of false alarms, and they cannot be accumulated across multiple images without creating ambiguity in their interpretation. Furthermore, quantitative and qualitative evaluation is often mixed resulting in ambiguous measures.
机译:评估对象检测算法是一项艰巨的任务:通常通过将检测到的对象的边界框与地面真实对象的边界框进行比较来评估检测结果。从这两个矩形的重叠区域计算出常用的精度和召回率。但是,这些措施有几个缺点:它们无法提供有关正确检测到的物体的比例和错误警报数量的直观信息,并且它们不能在不误解的情况下跨多个图像进行累积。此外,定量和定性评估常常混杂在一起,导致度量不明确。

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