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Design of Smart Device Assistive Emergency WayFinder Using Vision Based Emergency Exit Sign Detection  

Lee, Minwoo (서울과학기술대학교 나노IT디자인융합대학원 정보통신미디어공학전공)
Mariappan, Vinayagam (서울과학기술대학교 나노IT디자인융합대학원 정보통신미디어공학전공)
Mfitumukiza, Joseph (서울과학기술대학교 미디어IT공학과)
Lee, Junghoon (동서울대학교 전기정보제어과)
Cho, Juphil (군산대학교 IT융합통신공학전공)
Cha, Jaesang (서울과학기술대학교 나노IT디자인융합대학원 정보통신미디어공학전공)
Publication Information
Journal of Satellite, Information and Communications / v.12, no.1, 2017 , pp. 101-106 More about this Journal
Abstract
In this paper, we present Emergency exit signs are installed to provide escape routes or ways in buildings like shopping malls, hospitals, industry, and government complex, etc. and various other places for safety purpose to aid people to escape easily during emergency situations. In case of an emergency situation like smoke, fire, bad lightings and crowded stamped condition at emergency situations, it's difficult for people to recognize the emergency exit signs and emergency doors to exit from the emergency building areas. This paper propose an automatic emergency exit sing recognition to find exit direction using a smart device. The proposed approach aims to develop an computer vision based smart phone application to detect emergency exit signs using the smart device camera and guide the direction to escape in the visible and audible output format. In this research, a CAMShift object tracking approach is used to detect the emergency exit sign and the direction information extracted using template matching method. The direction information of the exit sign is stored in a text format and then using text-to-speech the text synthesized to audible acoustic signal. The synthesized acoustic signal render on smart device speaker as an escape guide information to the user. This research result is analyzed and concluded from the views of visual elements selecting, EXIT appearance design and EXIT's placement in the building, which is very valuable and can be commonly referred in wayfinder system.
Keywords
Emergency Exit Signs; LED; CAMShift Object Tracking; WayFinder; Computer Vision; OCR; Image Processing; Template Matching; Text-to-Speech;
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