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ASYSST: A framework for synopsis synthesis empowering visually impaired
Published in Association for Computing Machinery, Inc
Pages: 17 - 24
In an indoor scenario, the visually impaired do not have the information about the surroundings and finds it difficult to navigate from room to room. The sensor-based solutions are expensive and may not always be comfortable for the end users. In this paper, we focus on the problem of synthesis of textual description from a given floor plan image to assist the visually impaired. The textual description, in addition to a text reading software, can aid the visually impaired person while moving inside a building. In this work, for the first time, we propose an end to end framework (ASYSST) for textual description synthesis from digitized building floor plans. We have introduced a novel Bag of Decor (BoD) feature to learn 5 classes of a room from 1355 samples under a supervised learning paradigm. These learned labels are fed into a description synthesis framework to yield a holistic description of a floor plan image. Experimental analysis of real publicly available floor plan data-set proves the superiority of our framework. © 2018 Association for Computing Machinery.