Third Eye: A Shopping Assistant for the Visually Impaired
Abstract
Through a combination of wearable cameras, hardware accelerators, and algorithms, a vision-based automatic shopping assistant allows users with limited or no sight to select products from grocery shelves.
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Computer vision techniques use extensive computation power.
“Use extensive computation power”
From Making Shopping Easy for People with Visual Impairment Using Mobile Assistive Technologies (2019) · cites this paper as [41]
Computer vision techniques have inconsistent performance in real-world environments because of factors such as motion blur.
“Inconsistent performance in real-world environments because of factors such as motion blur”
From Making Shopping Easy for People with Visual Impairment Using Mobile Assistive Technologies (2019) · cites this paper as [41]
Most computer vision techniques can be installed easily on smartphones.
“Most of them can be installed easily on smartphones”
From Making Shopping Easy for People with Visual Impairment Using Mobile Assistive Technologies (2019) · cites this paper as [41]
PVI need to take many good quality photos, which is hard for them.
“PVI need to take many good quality photos that is hard for them”
From Making Shopping Easy for People with Visual Impairment Using Mobile Assistive Technologies (2019) · cites this paper as [41]
Computer vision techniques are cost-effective as they need little or no infrastructure.
“Cost-effective as they need little or no infrastructure”
From Making Shopping Easy for People with Visual Impairment Using Mobile Assistive Technologies (2019) · cites this paper as [41]
CV techniques have high cost, require a camera, can scan multiple items, require line of sight, and their range depends on the camera.
“| CV techniques | High | Camera | Multiple | Yes | Depends on camera | - |”
From Making Shopping Easy for People with Visual Impairment Using Mobile Assistive Technologies (2019) · cites this paper as [41]
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- Authors
- Zientara, P. A., Lee, S., Smith, G. H., Brenner, R., Itti, L., Rosson, M. B., Carroll, J. M., Irick, K. M., & Narayanan, V.
- Affiliations
- Pennsylvania State University (US)
- University of Southern California (US)
- Venue
- Computer
- Published
- 2017-02
- Volume
- 50
- Issue
- 2
- Pages
- 16-24
- ISSN
- 0018-9162 (ISSN-L)
- OpenAlex
- W2587151053
- Cited by
- 59
- References
- 10
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 7 · 2023: 6 · 2022: 11 · 2021: 5 · 2020: 8 · 2019: 10 · 2018: 4 · 2017: 2
- FWCI
- 18.49
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Computer (publishedVersion)
- Funders
- National Science Foundation
- Topics
- Health Sciences › Health Professions › Occupational Therapy › Assistive Technology in Communication and Mobility
- Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Keywords
- visually impaired people, shopping assistant, wearable cameras, hardware accelerators, grocery shopping, assistive technology, low vision
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