Decision-Point Panorama-Based Indoor Navigation

Decision-Point
Panorama-Based Indoor Navigation
Andreas Möller, Matthias Kranz,
Luis Roalter, Stefan Diewald, Kåre Synnes

MCPT Workshop on Eurocast 2013, February 15, 2013

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

Overview

Motivation: Vision-Based Localization

UI Concept and First Evaluation

Decision-Point Based Navigation

User Study

Discussion and Future Work

15.2.2013 A. Möller, M. Kranz, L. Roalter, S. Diewald, K. Synnes


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



Vision-Based Localization Live features

§  Principle
□  Comparing of query images, taken with
camera, to reference images based on
visual features
§  Advantages
□  No infrastructure and augmentation of the environment needed
□  Immune to disturbances (reflection/refraction…)
□  Works with existing
(modern) hardware



HCI Perspective: Interaction Concept
§  Augmented Reality View for intuitiveness
□  But: Consequence when location estimate
is inaccurate:
wrong overlays!

?

§  Permanent re-localization during path required
□  High computational effort
□  Uncomfortable camera pose
□  Not all scenes adequate for visual localization
(sometimes insufficient features for algorithm)



Interaction Concept (cont.)
Instead:
§  Re-localization from time to time
(when possible)
□  Estimation of intermediate position
with odometry (device sensors)
□  More comfortable usage
§  “Virtual Reality” View
□  Regularly show 360° panorama images
of the environment with embedded navigation
instructions (those panoramas are already available
from reference images)
□  More robust: user matches virtual and real world



Initial User Study
§  Comparison of
Augmented Reality and
Virtual Reality
§  Simulation of different levels
of accuracy
§  Survey of user preferences

See Full Paper:
A. Möller, M. Kranz, R. Huitl, S. Diewald, L. Roalter
A Mobile Indoor Navigation System Interface
Adapted to Vision-Based Localization
In: 11th Intl. Conf. on Mobile and
Ubiquitous Multimedia (MUM 2012)



Initial User Study: Summary
§  Panoramas provide better guidance when location estimate is
inaccurate than Augmented Reality
§  But: Subjects experienced frequent changes (~2m) as irritating, as
□  Shown locations are not always correct
□  Locations sometimes do not look like in reality
□  Frequent changes in the UI are visually straining
§  Subjects manage finding their goal, also when not looking at the
screen all the time

§  How to improve?
□  Reduce frequent visual changes
□  Simplify match between panoramas and real world (problem of
misplaced panoramas?)


Decision-Point Based Navigation (DPBN)
§  Show only panoramas of decision points
§  Compliance with familiar mental model of self-orientation
§  Users can always re-localize and retrieve the panorama
of their current location
§  High error tolerance
§  Offline usage possible (by swiping through list of route instructions)



Decision-Point Based Navigation (DPBN)
§  Show only panoramas of decision points
§  Compliance with familiar mental model of self-orientation
§  Users can always re-localize and retrieve the panorama
of their current location
§  High error tolerance
§  Offline usage possible



User Study: Research Questions
§  RQ1: Does DPBN have an effect on efficiency?
Are users as fast as with continuous panoramas?

§  RQ2: Is DPBN more convenient than continuous panoramas?
What mode do users prefer? How well do they feel guided?

§  RQ3: What usage patterns can be identified?
What do we learn for designing an “ideal” route description?



User Study – Quick Facts
3 conditions
-  Continuous panoramas (automatic *) * Wizard of Oz

-  Decision points (automatic *)
-  Decision points (manual navigation)

3 routes (avoidance of learning effects)
Measured data: time, user behavior, questionnaires

12 Participants, 75% male, 25% female, average 25 years
Within-subjects design

75% own a smartphone, only one has experience with
indoor navigation
Source: iconsdb.com



Results: RQ1
Average Time per Mode
350
300
Time in seconds

250
200
Difference
150 not
significant 263
100 196 208

50
0
Continuous Decision-Point Decision-Point
(automatic) (automatic) (manual)



Results: RQ2
I found the method pleasing to use.

5: fully agree
1: fully disagree

- Median
+ Mean



Results: RQ2
I felt guided well to the goal.

5: fully agree
1: fully disagree

- Median
+ Mean



Results: RQ2
Panoramas of decision
points are sufficient for Which system would you choose?
orientating

8%
Continuous
17% (automatic)
Decision-Point
(automatic)
Decision-Point
75% (manual)

5: fully agree
1: fully disagree



Results: RQ3
Participant 12 - Path 1

40

30
Distance (m)

20

10

0
20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340

Time (s)

swipe relocalize Δd position



Results: RQ3
60

50

40

30

20

10
Distance (m)

0
20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340
-10

-20

-30

-40

-50

-60
Time (s)




Results: RQ3

30

20
Distance (m)

10

0
20 40 60 80 100 120 140 160 180 200 220

-10

-20

Time (s)




Results: RQ3 – Manual Mode
§  Average numbers
□  52.5 continuous locations (automatic, continuous mode)
□  10.3 decision points (automatic, decision-point mode)
□  15.3 manual swipes
□  9.3 times relocalized
§  Different usage patterns/strategies
□  Showing “ahead” panoramas, no use of automatic re-localization
□  Frequent use of re-localization, (sometimes only in parts of the
route) – equivalent to continuous panorama mode
□  “Memorizing” of the entire route not observed, subjects only
looked at the “next” panorama location



Discussion
§  Subjects were equally fast with DPBN as
with continuous panoramas (RQ1)
§  Subjects felt guided better with continuous panoramas (RQ2)
□  Due to more certainty whether they are on the right way
□  Confirmed by frequent swipes and re-localizations in manual mode

§  DPBN is desirable from a technical point of view (reliability…), but
acceptance must be increased
§  Requires stronger confirmation whether subjects are (still) on the right
way



How could this be achieved?
(Lessons learned)
§  Compromise between continuous mode and DPBN as it is now

§  Distance information
§  Verification when decision point was passed
§  Add intermediate landmarks in decision point mode
□  Especially if decision point lies too far away (distance threshold)
§  Simplify the mapping of picture content to real environment
□  Highlight significant objects in panorama



Summary and Outlook
§  With Decision-Point Based Navigation, we have presented
a novel interface for visual indoor navigation
□  Very robust in case of localization inaccuracy
□  Works even if localization fails (manual mode)
□  Supports users’ mental model of navigation (landmarks)
§  Real-world study results
□  DPBN as efficient as full panorama navigation
□  DPBN needs more information to reduce users’ uncertainty
(landmarks, confirmations) to increase satisfaction
§  Future work
□  See previous slide ;-)
□  Identification of good candidates for (additional) key points



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 Reference
§  Please find the associated paper at:
https://vmi.lmt.ei.tum.de/publications/2013/MCPT2013-
IndoorNav_preprint.pdf

§  Please cite this work as follows:
§  A. Möller, M. Kranz, L. Roalter, S. Diewald, Kåre Synnes
Decision-Point Panorama-Based Indoor Navigation
In: 14th International Conference on Computer Aided Systems
Theory (EUROCAST 2013), pp. 325-326, Las Palmas de Gran
Canaria, Spain, February 2013



If you use BibTex, please use the following
entry to cite this work:

@INPROCEEDINGS{MCPT13IndoorNav,
author = {Andreas M{"o}ller and Matthias Kranz and Luis Roalter and Stefan Diewald},
title = {{Decision-Point Panorama-Based Indoor Navigation}},
booktitle = {14th International Conference on Computer Aided Systems Theory (EUROCAST 2013)},
editor = {Alexis Quesada-Arencibia and Jos'{e} Carlos Rodriguez and Roberto Moreno-Diaz jr. and Roberto Moreno-Diaz},
year = {2013},
month = feb,
pages = {325--326},
ISBN = {978-84-695-6971-9},
location = {Las Palmas de Gran Canaria, Spain},
}


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