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CamScan, an Application to Identify Everyday Objects for Users with Vision Impairments

Published: 07 September 2015 Publication History

Abstract

Technology can help users with blindness or vision impairments to overcome everyday challenges. Furthermore, the widespread acceptance and use of mobile phones, makes it suitable to develop accessible technologies on these devices. One common problem that users with vision impairments face is the identification of everyday objects, especially when these objects have a similar shape as others (e.g. cans, CDs). Different works have tackled this problem including object recognition and remote workers on the internet who answer questions on the image sent. This work approaches this problem and presents new features with the aim of bringing new capture possibilities and then discusses the findings

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Cited By

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  • (2020)Addressing Inattentional Blindness with Smart Eyewear and Vibrotactile Feedback on the Finger, Wrist, and ForearmProceedings of the 19th International Conference on Mobile and Ubiquitous Multimedia10.1145/3428361.3432080(329-331)Online publication date: 22-Nov-2020

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      cover image ACM Other conferences
      Interacción '15: Proceedings of the XVI International Conference on Human Computer Interaction
      September 2015
      287 pages
      ISBN:9781450334631
      DOI:10.1145/2829875
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      • Universitat Politècnica de Catalunya: Universitat Politècnica de Catalunya

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 07 September 2015

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      Author Tags

      1. Assistive technologies
      2. Capture
      3. RGB-D
      4. object identification
      5. vision impairments

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      Overall Acceptance Rate 109 of 163 submissions, 67%

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      View all
      • (2020)Addressing Inattentional Blindness with Smart Eyewear and Vibrotactile Feedback on the Finger, Wrist, and ForearmProceedings of the 19th International Conference on Mobile and Ubiquitous Multimedia10.1145/3428361.3432080(329-331)Online publication date: 22-Nov-2020

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