Header

UZH-Logo

Maintenance Infos

“Turn left after the WC, and use the lift to go to the 2nd floor”—Generation of landmark-based route instructions for indoor navigation


Fellner, Irene; Huang, Haosheng; Gartner, Georg (2017). “Turn left after the WC, and use the lift to go to the 2nd floor”—Generation of landmark-based route instructions for indoor navigation. ISPRS International Journal of Geo-Information, 6(6):183.

Abstract

People in unfamiliar environments often need navigation guidance to reach a destination. Research has found that compared to outdoors, people tend to lose orientation much more easily within complex buildings, such as university buildings and hospitals. This paper proposes a category-based method to generate landmark-based route instructions to support people’s wayfinding activities in unfamiliar indoor environments. Compared to other methods relying on detailed instance-level data about the visual, semantic, and structural characteristics of individual spatial objects, the proposed method relies on commonly available data about categories of spatial objects, which exist in most indoor spatial databases. With this, instructions like “Turn right after the second door, and use the elevator to go to the second floor” can be generated for indoor navigation. A case study with a university campus shows that the method is feasible in generating landmark-based route instructions for indoor navigation. More importantly, compared to metric-based instructions (i.e., the benchmark for indoor navigation), the generated landmark-based instructions can help users to unambiguously identify the correct decision point where a change of direction is needed, as well as offer information for the users to confirm that they are on the right way to the destination.

Abstract

People in unfamiliar environments often need navigation guidance to reach a destination. Research has found that compared to outdoors, people tend to lose orientation much more easily within complex buildings, such as university buildings and hospitals. This paper proposes a category-based method to generate landmark-based route instructions to support people’s wayfinding activities in unfamiliar indoor environments. Compared to other methods relying on detailed instance-level data about the visual, semantic, and structural characteristics of individual spatial objects, the proposed method relies on commonly available data about categories of spatial objects, which exist in most indoor spatial databases. With this, instructions like “Turn right after the second door, and use the elevator to go to the second floor” can be generated for indoor navigation. A case study with a university campus shows that the method is feasible in generating landmark-based route instructions for indoor navigation. More importantly, compared to metric-based instructions (i.e., the benchmark for indoor navigation), the generated landmark-based instructions can help users to unambiguously identify the correct decision point where a change of direction is needed, as well as offer information for the users to confirm that they are on the right way to the destination.

Statistics

Citations

Altmetrics

Downloads

11 downloads since deposited on 03 Nov 2017
11 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Date:2017
Deposited On:03 Nov 2017 14:42
Last Modified:19 Feb 2018 09:09
Publisher:MDPI Publishing
ISSN:2220-9964
Additional Information:Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers.
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.3390/ijgi6060183

Download

Download PDF  '“Turn left after the WC, and use the lift to go to the 2nd floor”—Generation of landmark-based route instructions for indoor navigation'.
Preview
Content: Published Version
Language: English
Filetype: PDF
Size: 3MB
View at publisher
Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)