QfaR: Location-Guided Scanning of Visual Codes from Long Distances-Reference-Cited by-同舟云学术

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QfaR: Location-Guided Scanning of Visual Codes from Long Distances

Published:2023-07-10 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 29th Annual International Conference on Mobile Computing and Networking
language:
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Author:

Ma Sizhuo¹^ORCID,Wang Jian²^ORCID,Chen Wenzheng³^ORCID,Banerjee Suman⁴^ORCID,Gupta Mohit⁵^ORCID,Nayar Shree²^ORCID

Affiliation:

1. Snap Inc., New York, New York, United States

2. Snap Inc., New York, New York, USA

3. University of Toronto, Toronto, Ontario, Canada

4. University of Wisconsin-Madison, Madison, Wisconsin, United States

5. University of Wisconsin-Madison, Madison, Wisconsin, USA

Funder

U.S. Department of Commerce

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3570361.3592497

Reference25 articles.

1. YOLO v3-Tiny: Object Detection and Recognition using one stage improved model

2. Multiple Resolution Machine Readable Symbols;Batterman Eric P;US Patent,1992

3. G. Bradski . 2000. The OpenCV Library. Dr. Dobb's Journal of Software Tools ( 2000 ). G. Bradski. 2000. The OpenCV Library. Dr. Dobb's Journal of Software Tools (2000).

4. Roberto Brunelli . 2009. Template Matching Techniques in Computer Vision: Theory and Practice . Wiley Publishing . Roberto Brunelli. 2009. Template Matching Techniques in Computer Vision: Theory and Practice. Wiley Publishing.

5. Multi-Resolution Optical Codes;Cok Ronald Steven;US Patent,2013

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