Abstract
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.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the IEEE Workshop on Signal Processing Systems, SiPS 2018 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 112-117 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781538663189 |
| DOIs | |
| State | Published - Dec 31 2018 |
| Event | 2018 IEEE Workshop on Signal Processing Systems, SiPS 2018 - Cape Town, South Africa Duration: Oct 21 2018 → Oct 24 2018 |
Publication series
| Name | IEEE Workshop on Signal Processing Systems, SiPS: Design and Implementation |
|---|---|
| Volume | 2018-October |
| ISSN (Print) | 1520-6130 |
Conference
| Conference | 2018 IEEE Workshop on Signal Processing Systems, SiPS 2018 |
|---|---|
| Country | South Africa |
| City | Cape Town |
| Period | 10/21/18 → 10/24/18 |
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All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering
- Signal Processing
- Applied Mathematics
- Hardware and Architecture
Cite this
}
Indoor Navigation using Text Extraction. / Eden, Jake; Kawchak, Thomas; Narayanan, Vijaykrishnan.
Proceedings of the IEEE Workshop on Signal Processing Systems, SiPS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 112-117 8598409 (IEEE Workshop on Signal Processing Systems, SiPS: Design and Implementation; Vol. 2018-October).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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.
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U2 - 10.1109/SiPS.2018.8598409
DO - 10.1109/SiPS.2018.8598409
M3 - Conference contribution
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.
ER -