Scene text access: A comparison of mobile OCR modalities for blind users

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Abstract

We present a study with seven blind participants using three different mobile OCR apps to find text posted in various indoor environments. The first app considered was Microsoft SeeingAI in its Short Text mode, which reads any text in sight with a minimalistic interface. The second app was Spot+OCR, a custom application that separates the task of text detection from OCR proper. Upon detection of text in the image, Spot+OCR generates a short vibration; as soon as the user stabilizes the phone, a high-resolution snapshot is taken and OCR-processed. The third app, Guided OCR, was designed to guide the user in taking several pictures in a 360ºspan at the maximum resolution available by the camera, with minimum overlap between pictures. Quantitative results (in terms of true positive ratios and traversal speed) were recorded. Along with the qualitative observation and outcomes from an exit survey, these results allow us to identify and assess the different strategies used by our participants, as well as the challenges of operating these systems without sight.

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APA

Neat, L., Peng, R., Qin, S., & Manduchi, R. (2019). Scene text access: A comparison of mobile OCR modalities for blind users. In International Conference on Intelligent User Interfaces, Proceedings IUI (Vol. Part F147615, pp. 197–207). Association for Computing Machinery. https://doi.org/10.1145/3301275.3302271

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