An Evaluation of General-Purpose Optical Character Recognizers and Digit Detectors for Race Bib Number Recognition

Abstract

Bib numbers are used in mass competitions to identify participants, especially in long-distance races where runners commonly wear tags to verify that they pass mandatory checkpoints. In this paper, we delve deeper into the use of existing computer vision techniques for recognizing the digits present in bib numbers. Our analysis of bib recognition involves evaluating OCRs (Optical Character Recognition) techniques and a YOLOv7 digit detector on two public datasets: RBNR and TGCRBNW. The results reveal that the former scenario is solvable, while the latter presents extremely in-the-wild challenges. However, the findings suggest that more than relying solely on RBN for runner identification, other appearance-based cues, e.g., clothing and accessories, may be required due to various circumstances, such as occlusion or incomplete bib recognition. In any case, all those cues do not necessarily imply that the same person is wearing the RBN across the competition track, as they are not biometric traits.