TY - GEN
T1 - Indoor Navigation using Text Extraction
AU - Eden, Jake
AU - Kawchak, Thomas
AU - Narayanan, Vijaykrishnan
PY - 2018/12/31
Y1 - 2018/12/31
N2 - In this paper, we explore the possibility of harnessing text extraction to perform localization for a visually impaired grocery shopper to help the shopper navigate through a grocery store. The extraction of environmental text is performed only after more traditional guidance techniques are employed to first bring the user to the text-rich aisles of a grocery store. This idea is built upon the need for both text extraction and localization in a visual assistance pipeline. For instance, typical visual assistance pipelines attempt to solve a number of problems: indoor localization and navigation, classification of an aisle's products, and potentially contextual information retrieval based on local environmental text (to, say, determine a product's price). However, prior art does not consider how text might also augment localization. Thus, this paper explores the viability of introducing text into such a seemingly disjoint problem space and ultimately concludes that environmental text extraction can enhance indoor localization by providing course-grained accuracy.
AB - In this paper, we explore the possibility of harnessing text extraction to perform localization for a visually impaired grocery shopper to help the shopper navigate through a grocery store. The extraction of environmental text is performed only after more traditional guidance techniques are employed to first bring the user to the text-rich aisles of a grocery store. This idea is built upon the need for both text extraction and localization in a visual assistance pipeline. For instance, typical visual assistance pipelines attempt to solve a number of problems: indoor localization and navigation, classification of an aisle's products, and potentially contextual information retrieval based on local environmental text (to, say, determine a product's price). However, prior art does not consider how text might also augment localization. Thus, this paper explores the viability of introducing text into such a seemingly disjoint problem space and ultimately concludes that environmental text extraction can enhance indoor localization by providing course-grained accuracy.
UR - http://www.scopus.com/inward/record.url?scp=85061403100&partnerID=8YFLogxK
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U2 - 10.1109/SiPS.2018.8598409
DO - 10.1109/SiPS.2018.8598409
M3 - Conference contribution
AN - SCOPUS:85061403100
T3 - IEEE Workshop on Signal Processing Systems, SiPS: Design and Implementation
SP - 112
EP - 117
BT - Proceedings of the IEEE Workshop on Signal Processing Systems, SiPS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE Workshop on Signal Processing Systems, SiPS 2018
Y2 - 21 October 2018 through 24 October 2018
ER -