An Evaluation of OCR on Egocentric Data

• URL: http://arxiv.org/abs/2206.05496v1
• Date: Sat, 11 Jun 2022 10:37:20 GMT
• Title: An Evaluation of OCR on Egocentric Data
• Authors: Valentin Popescu, Dima Damen, Toby Perrett
• Abstract summary: In this paper, we evaluate state-of-the-art OCR methods on Egocentric data. We demonstrate that existing OCR methods struggle with rotated text, which is frequently observed on objects being handled. We introduce a simple rotate-and-merge procedure which can be applied to pre-trained OCR models that halves the normalized edit distance error.
• Score: 30.637021477342035
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this paper, we evaluate state-of-the-art OCR methods on Egocentric data. We annotate text in EPIC-KITCHENS images, and demonstrate that existing OCR methods struggle with rotated text, which is frequently observed on objects being handled. We introduce a simple rotate-and-merge procedure which can be applied to pre-trained OCR models that halves the normalized edit distance error. This suggests that future OCR attempts should incorporate rotation into model design and training procedures.

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