VisBuddy -- A Smart Wearable Assistant for the Visually Challenged
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Abstract (arXiv)
Vision plays a crucial role in comprehending the world around us. More than 85% of the external information is obtained through the vision system. It influences our mobility, cognition, information access, and interaction with the environment and other people. Blindness prevents a person from gaining knowledge of the surrounding environment and makes unassisted navigation, object recognition, obstacle avoidance, and reading tasks significant challenges. Many existing systems are often limited by cost and complexity. To help the visually challenged overcome these difficulties faced in everyday life, we propose VisBuddy, a smart assistant to help the visually challenged with their day-to-day activities. VisBuddy is a voice-based assistant where the user can give voice commands to perform specific tasks. It uses the techniques of image captioning for describing the user's surroundings, optical character recognition (OCR) for reading the text in the user's view, object detection to search and find the objects in a room and web scraping to give the user the latest news. VisBuddy has been built by combining the concepts from Deep Learning and the Internet of Things. Thus, VisBuddy serves as a cost-efficient, powerful, all-in-one assistant for the visually challenged by helping them with their day-to-day activities.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 6 of its 20 references that are in the map. First posted on arXiv 17 Aug 2021.
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References · 6
- 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
- 2015Rethinking the Inception Architecture for Computer Visioncited by 5,475
- 2018MobileNetV2: Inverted Residuals and Linear Bottleneckscited by 4,795
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- 2014Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modelingcited by 2,367
- 2015Show, Attend and Tell: Neural Image Caption Generation with Visual Attentioncited by 1,423
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