Text Detection in Stores Using a Repetition Prior
Abstract
Text detection in stores has valuable applications that could transform the shopping experience, yet cluttered store environments present distinct challenges for existing techniques. We propose a strategy for text detection in stores that exploits a repetition prior. Leveraging the fact that shops typically display multiple instances of the same product on the shelf, our approach localizes text regions with a global view of the image, preferring instances that have repeated support in the scene. On two challenging real-world datasets taken with a mobile phone and wearable camera, we demonstrate our method's substantial advantages compared to several state-of-the-art techniques in grocery store environments.
Cite
Text
Xiong and Grauman. "Text Detection in Stores Using a Repetition Prior." IEEE/CVF Winter Conference on Applications of Computer Vision, 2016. doi:10.1109/WACV.2016.7477575Markdown
[Xiong and Grauman. "Text Detection in Stores Using a Repetition Prior." IEEE/CVF Winter Conference on Applications of Computer Vision, 2016.](https://mlanthology.org/wacv/2016/xiong2016wacv-text/) doi:10.1109/WACV.2016.7477575BibTeX
@inproceedings{xiong2016wacv-text,
title = {{Text Detection in Stores Using a Repetition Prior}},
author = {Xiong, Bo and Grauman, Kristen},
booktitle = {IEEE/CVF Winter Conference on Applications of Computer Vision},
year = {2016},
pages = {1-9},
doi = {10.1109/WACV.2016.7477575},
url = {https://mlanthology.org/wacv/2016/xiong2016wacv-text/}
}