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Describing image focused in cognitive and visual details for visually impaired people: An approach to generating inclusive paragraphs

arXiv 2202.05331 ↗First posted 10 Feb 2022cs.CV cs.AI cs.CLcited by 0

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Abstract (arXiv)

Several services for people with visual disabilities have emerged recently due to achievements in Assistive Technologies and Artificial Intelligence areas. Despite the growth in assistive systems availability, there is a lack of services that support specific tasks, such as understanding the image context presented in online content, e.g., webinars. Image captioning techniques and their variants are limited as Assistive Technologies as they do not match the needs of visually impaired people when generating specific descriptions. We propose an approach for generating context of webinar images combining a dense captioning technique with a set of filters, to fit the captions in our domain, and a language model for the abstractive summary task. The results demonstrated that we can produce descriptions with higher interpretability and focused on the relevant information for that group of people by combining image analysis methods and neural language models.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 19 of its 33 references that are in the map. First posted on arXiv 10 Feb 2022.

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References · 19

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7 more
  1. 2021CPTR: Full Transformer Network for Image Captioningcited by 55
  2. 2016Dense Captioning with Joint Inference and Visual Contextcited by 40
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  6. 2020Image Captioning as an Assistive Technology: Lessons Learned from VizWiz 2020 Challengecited by 17
  7. 2018Diverse and Coherent Paragraph Generation from Imagescited by 13

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