A Mobile Indoor Navigation System Interface Adapted to Vision-Based Localization

A Mobile Indoor Navigation System Interface
Adapted to Vision-Based Localization
Andreas Möller1, Matthias Kranz2, Robert Huitl1, Stefan Diewald1, Luis Roalter1
1Technische Universität München, Germany
2Luleå University of Technology, Department of Computer Science,

Electrical and Space Engineering, Luleå, Sweden

MUM 2012, Ulm, Germany

Institute for Media Technology
Distributed Multimodal Information Processing Group Technische Universität München

Outline
§ Motivation for Vision-Based Navigation
§ Challenges
§ Proposed User Interface Concepts
§ Evaluation
§ Discussion and Conclusion

04.12.2012 A. Möller, M. Kranz, R. Huitl, S. Diewald, L. Roalter 2


Background and Motivation
§ Location information still the
most important contextual information
§ Indoor localization is a hot topic
and useful for a lot of scenarios:
□ Airports
□ Hospitals
□ Conference venues
□ Large environments
§ Various indoor localization methods
possible:
□ WLAN/cell-based localization
□ Sensor-based localization
□ Beacon-based localization
□ Vision-based localization



Why vision-based localization?
Live features
§ Compare query image to reference data set
§ Use existing features in the environment
§ No additional augmentation needed
§ Modern devices are equipped with a camera
and powerful processor



Challenges of Vision-Based Localization
§ Query images need to be distinctive
□ Repeating structures throughout the environment (e.g. corridors)
□ Little visual features (e.g. uniform walls)

§ Orientation of the user’s smartphone
□ Good candidates for query images (windows, adverts, posters) are
typically found in eye height
□ In a typical pose, user holds the device in a way that it points at
the floor

§ User interface needs to address those challenges



User Interface Concept
Our
contrib
§ No 1 Challenge: Localization inaccuracy ution:
Addres
□ When insufficient number of features problem s
from
in the query image a UI
perspe
ctive
§ Solution A: Adaption of the user interface
□ Augmented Reality (AR) with a live view of the environment
□ Virtual Reality (VR) with panorama images
(compare to Google Street View)
taken in advance

§ Solution B: Corrective actions
□ The user needs to point at interesting regions with the camera



Augmented Reality (AR)

• Display the live camera image

• Impose navigation instructions
over the image

• Smartphone held in
eye height

• Direct match of information and
the real environment



Virtual Reality (VR)

• Uses preloaded panorama
images

• Navigation instructions are
drawn in panorama

• Smartphone can be directed
to the ground

• User matches environment
and virtual reality



Pointing Towards Discriminative Areas



Highlighting Objects of Interest



Research Questions
§ RQ1: Which concept (AR or VR) is preferable in terms of perceived
accuracy?

§ RQ2: Which concept (AR or VR) is preferred by users?

§ RQ3: Which visualizations are appropriate to acquire sufficient visual
features?

§ RQ4: Can object highlighting be improved with a soft border
visualization?



Methodology
§ Online Survey
§ Videos and images of mockup system
§ 81 participants (18-59 years) recruited via Mobileworks


Virtual Reality

Perceived Accuracy of Virtual Reality and Augmented Reality Views
RQ1: Perceived accuracy
No Error Orientation Error Location Error Loc.+Ori. Error
Response Std.Dev. Response Std.Dev. Response Std.Dev. Response Std.Dev.
1: 2.5 0.9 0.8 2.0 1.7 1.5 0.6 2.0
§ Simulated error conditions 1.4
1.7 1.6 1.8 1.4 1.8 1.0 1.7
2:
□ No Error 1.0
2.4
1.7 1.5
0.2
1.1
2.1
1.8
1.2
□ Orientation Error
1.3
1.8
1.7
0.4
0.9
2.1
1.8
3: □ Location Error
2.3 1.0 -0.2 2.0 □ Both Errors 1.9
0.4 -0.5 1.9
1.8 1.4 1.4 1.6 1.4 1.7 0.9 1.8

Augmented Reality 1: The system seemed to know well my location.
2: The system seemed to know well my orientation.
Virtual Reality 3: I perceived the navigation instructions as correct.

Perceived Accuracy of Virtual Reality and Augmented Reality Views
No Error Orientation Error Location Error Loc.+Ori. Error
Response Std.Dev. Response Std.Dev. Response Std.Dev. Response Std.Dev.
2.3 1.0 -0.2 2.0 0.4 1.9 -0.5 1.9
1.8 1.4 1.4 1.6 1.4 1.7 0.9 1.8

Augmented Reality
-3: strongly disagree
Virtual Reality +3: strongly agree



RQ2: User Preferences
§ In total, AR more popular with users than VR

+3: strongly agree



RQ3: Feature Indicator
§ Clarity of the indicator‘s a)
meaning b)
c)
-3: strongly disagree d)
+3: strongly agree

a) b)

c) d)



RQ4: Highlighting
methods
§ Objects of interest
highlighting
□ Potentially feature-rich
□ Interaction points for
location-based services
§ Two types
□ Frame
□ Soft border
§ Both equally raise attention,
but Frame distracts more

+3: strongly agree



Discussion
§ Accuracy perception through the interface
□ VR beneficial for lower localization accuracy
□ AR preferred for reliable estimate
§ Feature indicators and object highlights potentially contribute to good
reference images
§ Situational use
□ VR for 45° angle
□ Less features visible
□ Less accuracy required
□ AR when holding the phone up
□ Target to visual features
□ Highlight objects of interaction



Future and
Ongoing Work
§ Evaluating interfaces in the
real world
§ Modeling the system’s
and user’s state
□ Localization accuracy
□ Location/environment
□ User context
□ User mental model
□ …



Thank you for your attention!
Questions?

?
?
andreas.moeller@tum.de
www.vmi.ei.tum.de/team/andreas-moeller.html

This research project has been supported by the space agency of the German Aerospace Center with
funds from the Federal Ministry of Economics and Technology on the basis of a resolution of the German
Bundestag under the reference 50NA1107.



Paper References
§ Please find the full paper at:
http://dx.doi.org/10.1145/2406367.2406372

§ Please cite this work as follows:
§ Andreas Möller, Matthias Kranz, Robert Huitl, Stefan Diewald, and Luis
Roalter. 2012. A mobile indoor navigation system interface adapted to
vision-based localization. In Proceedings of the 11th International
Conference on Mobile and Ubiquitous Multimedia (MUM '12). ACM, New
York, NY, USA, , Article 4 , 10 pages. DOI=10.1145/2406367.2406372
http://doi.acm.org/10.1145/2406367.2406372
§



Please use the following BibTex file:
§ @inproceedings{Moller:2012:MIN:2406367.2406372,
author = {M"{o}ller, Andreas and Kranz, Matthias and Huitl, Robert and Diewald,
Stefan and Roalter, Luis},
title = {A mobile indoor navigation system interface adapted to vision-based
localization},
booktitle = {Proceedings of the 11th International Conference on Mobile and
Ubiquitous Multimedia},
series = {MUM '12},
year = {2012},
isbn = {978-1-4503-1815-0},
location = {Ulm, Germany},
pages = {4:1--4:10},
articleno = {4},
numpages = {10},
url = {http://doi.acm.org/10.1145/2406367.2406372},
doi = {10.1145/2406367.2406372},
acmid = {2406372},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {augmented reality, indoor navigation, user interface, virtual
reality, vision-based localization},
}
[

A Mobile Indoor Navigation System Interface Adapted to Vision-Based Localization

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