Humans Disagree With the IoU for Measuring Object Detector Localization Error
O. Strafforello (TU Delft - Pattern Recognition and Bioinformatics, TNO)
Vanathi Rajasekart (Student TU Delft)
O.S. Kayhan (TU Delft - Pattern Recognition and Bioinformatics)
O. Inel (Universitat Zurich, TU Delft - Web Information Systems)
J.C. van Gemert (TU Delft - Pattern Recognition and Bioinformatics)
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Abstract
The localization quality of automatic object detectors is typically evaluated by the Intersection over Union (IoU) score. In this work, we show that humans have a different view on localization quality. To evaluate this, we conduct a survey with more than 70 participants. Results show that for localization errors with the exact same IoU score, humans might not consider that these errors are equal, and express a preference. Our work is the first to evaluate IoU with humans and makes it clear that relying on IoU scores alone to evaluate localization errors might not be sufficient.