SonoVision: A Computer Vision Approach for Helping Visually Challenged Individuals Locate Objects with the Help of Sound Cues
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Abstract (arXiv)
Locating objects for the visually impaired is a significant challenge and is something no one can get used to over time. However, this hinders their independence and could push them towards risky and dangerous scenarios. Hence, in the spirit of making the visually challenged more self-sufficient, we present SonoVision, a smart-phone application that helps them find everyday objects using sound cues through earphones/headphones. This simply means, if an object is on the right or left side of a user, the app makes a sinusoidal sound in a user's respective ear through ear/headphones. However, to indicate objects located directly in front, both the left and right earphones are rung simultaneously. These sound cues could easily help a visually impaired individual locate objects with the help of their smartphones and reduce the reliance on people in their surroundings, consequently making them more independent. This application is made with the flutter development platform and uses the Efficientdet-D2 model for object detection in the backend. We believe the app will significantly assist the visually impaired in a safe and user-friendly manner with its capacity to work completely offline. Our application can be accessed here https://github.com/MohammedZ666/SonoVision.git.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 5 of its 13 references that are in the map. First posted on arXiv 27 Dec 2025.
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References · 5
- 2020Knowledge Distillation: A Surveycited by 1,603
- 2021Grounded Language-Image Pre-trainingcited by 1,156
- 2019EfficientDet: Scalable and Efficient Object Detectioncited by 1,020
- 2016Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activationscited by 426
- 2022Towards Open-Set Object Detection and Discoverycited by 44
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