NDLI: SUGAMAN: describing floor plans for visually impaired by annotation learning and proximity-based grammar

Content Provider	IET Digital Library
Author	Goyal, Shreya Bhavsar, Satya Patel, Shreya Chattopadhyay, Chiranjoy Bhatnagar, Gaurav
Abstract	In this study, the authors propose a framework SUGAMAN (Supervised and Unified framework using Grammar and Annotation Model for Access and Navigation). SUGAMAN is a Hindi word meaning ‘easy passage from one place to another’. SUGAMAN synthesises textual description from a given floor plan image, usable by visually impaired to navigate by understanding the arrangement of rooms and furniture. It is the first framework for describing a floor plan and giving direction for obstacle-free movement within a building. The model learns five classes of room categories from 1355 room image samples under a supervised learning paradigm. These learned annotations are fed into a description synthesis framework to yield a holistic description of a floor plan image. Authors demonstrate the performance of various supervised classifiers on room learning and provided a comparative analysis of system generated and human-written descriptions. The contribution of this study includes a novel framework for description generation from document images with graphics while proposing a new feature representing the floor plans, text annotations for a publicly available data set, and an algorithm for door to door obstacle avoidance navigation. This work can be applied to areas like understanding floor plans and design of historical monuments, and retrieval.
Starting Page	2623
Ending Page	2635
Page Count	13
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 13, Nov (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/13
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.5627
Journal	IET Image Processing
Publisher Date	2019-09-18
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Aids For The Handicapped Annotation Learning Annotation Model Collision Avoidance Computational Linguistics Computer Assistance For Persons with Handicaps Computer Vision And Image Processing Technique Description Generation Document Image Processing Document Processing Technique Door to Door Obstacle Avoidance Navigation Algorithm Floor Plan Image Formal Languages Grammars Handicapped Aids Human-written Descriptions Knowledge Engineering Technique Learned Annotations Natural Language Processing Optical, Image And Video Signal Processing Proximity-based Grammar Real-world Floor Plan Image Room Image Sample Room Learning SUGAMAN Supervised Learning Supervised Learning Paradigm Text Analysis Text Annotations Text Description Synthesis Framework Visually Impaired Person
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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