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

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

Overview

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

Motivation: Vision-Based Localization

UI Concept and First Evaluation

Decision-Point Based Navigation

User Study

Discussion and Future Work


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

§  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

Live features



Overview





User Study



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


Overview





User Study



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



Overview





User Study



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 *) -  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

* Wizard of Oz


Results: RQ1

196 208 263

0

50

100

150

200

250

300

350

Continuous (automatic)

Decision-Point (automatic)

Decision-Point (manual)

Average Time per Mode


Tim

e in

sec

onds

Difference not

significant


Results: RQ2


I found the method pleasing to use.




5: fully agree 1: fully disagree

- Median + Mean


I felt guided well to the goal.




Results: RQ2



- Median + Mean


Which system would you choose?

Results: RQ2


75%

17%

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

Panoramas of decision points are sufficient for

orientating



0

10

20

30

40

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

Dis

tan

ce (

m)

Time (s)

Participant 12 - Path 1

swipe relocalize Δd position

Results: RQ3



-60

-50

-40

-30

-20

-10

0

10

20

30

40

50

60

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

Dis

tance

(m

)

Time (s)



Results: RQ3



-20

-10

0

10

20

30

20 40 60 80 100 120 140 160 180 200 220

Dis

tan

ce (

m)

Time (s)



Results: RQ3



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



Overview





User Study



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?

? ? [email protected]

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}, }

Decision-Point Panorama-Based Indoor Navigation

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