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arXiv · 2206.05496

An Evaluation of OCR on Egocentric Data

Valentin Popescu·Dima Damen·Toby Perrett
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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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Valentin Popescu, Dima Damen, Toby Perrett. 2022-06-11. An Evaluation of OCR on Egocentric Data. https://arxiv.org/abs/2206.05496

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