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In this paper, we propose SUGAMAN (Supervised and Unified framework usingGrammar and Annotation Model for Access and Navigation). SUGAMAN is a Hindiword meaning "easy passage from one place to another". SUGAMAN synthesizestextual description from a given floor plan image for the visually impaired. Avisually impaired person can navigate in an indoor environment using thetextual description generated by SUGAMAN. With the help of a text readersoftware, the target user can understand the rooms within the building andarrangement of furniture to navigate. SUGAMAN is the first framework fordescribing a floor plan and giving direction for obstacle-free movement withina building. We learn $5$ classes of room categories from $1355$ room imagesamples under a supervised learning paradigm. These learned annotations are fedinto a description synthesis framework to yield a holistic description of afloor plan image. We demonstrate the performance of various supervisedclassifiers on room learning. We also provide a comparative analysis of systemgenerated and human written descriptions. SUGAMAN gives state of the artperformance on challenging, real-world floor plan images. This work can beapplied to areas like understanding floor plans of historical monuments,stability analysis of buildings, and retrieval.

SUGAMAN: Describing Floor Plans for Visually Impaired by Annotation Learning and Proximity based Grammar