MobiMed: Comparing Object Identification Techniques on Smartphones

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With physical mobile interaction techniques, digital devices can make use of real-world objects in order to interact with them. In this paper, we evaluate and compare state-of-the-art interaction methods in an extensive survey with 149 participants and in a lab study with 16 participants regarding efficiency, utility and usability. Besides radio communication and fiducial markers, we consider visual feature recognition, reflecting the latest technical expertise in object identification. We conceived MobiMed, a medication package identifier implementing four interaction paradigms: pointing, scanning, touching and text search.
We identified both measured and perceived advantages and disadvantages of the individual methods and gained fruitful feedback from participants regarding possible use cases for MobiMed. Touching and scanning were evaluated as fastest in the lab study and ranked first in user satisfaction. The strength of visual search is that objects need not be augmented, opening up physical mobile interaction as demon- strated in MobiMed for further fields of application.

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MobiMed: Comparing Object Identification Techniques on Smartphones

  1. 1. Distributed Multimodal Information Processing Group Technische Universität München MobiMed: Comparing Object Identification Techniques on Smartphones Andreas Möller1, Stefan Diewald1, Luis Roalter1, Matthias Kranz2 1Technische Universität München, Germany 2Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Luleå, Sweden October 15, 2012 NordiCHI, Copenhagen, Denmark
  2. 2. Distributed Multimodal Information Processing Group Technische Universität MünchenOutline Background and Motivation Scenario and Prototype User Study Discussion and ConclusionOct 15, 2012 A. Möller, S. Diewald, L. Roalter, M. Kranz 2
  3. 3. Distributed Multimodal Information Processing Group Technische Universität MünchenBackground and Motivation•  Idea of bridging the gap between the physical and the virtual world for easier interaction and additional functionality –  Connect physical objects with virtual representations by tags (Want et al., 1999) –  Physical mobile interaction (Rukzio, 2006)•  Investigation and comparison of different interaction techniques done earlier, BUT: –  meanwhile outdated technologies (e.g. IR) –  older comparisons based on (nowadays) limited hardware (VGA cameras, small screens, slow mobile CPUs) –  new technologies have emerged (e.g. vision-based approaches) –  user knowledge and experience has changed Suggesting a new comparison of (state-of-the-art) interaction techniquesOct 15, 2012 A. Möller, S. Diewald, L. Roalter, M. Kranz 3
  4. 4. Distributed Multimodal Information Processing Group Technische Universität MünchenOutline Background and Motivation Scenario and Prototype User Study Discussion and ConclusionOct 15, 2012 A. Möller, S. Diewald, L. Roalter, M. Kranz 4
  5. 5. Distributed Multimodal Information Processing Group Technische Universität MünchenScenario for Physical Mobile Interaction•  MobiMed: identifying medication packages with the smartphone•  Target groups: active people pursuing a healthy lifestyle, elderly people•  Physical mobile interaction to get information on drugs –  package insert –  side effects –  active ingredients –  cross-correlationsOct 15, 2012 A. Möller, S. Diewald, L. Roalter, M. Kranz 5
  6. 6. Distributed Multimodal Information Processing Group Technische Universität MünchenInvestigated Interaction Types Touching Scanning (radio tags, e.g. NFC or RFID) (visual tags, e.g. bar codes) Pointing Text Input (tag-less vision-based identification) (e.g. name, ID, …)Oct 15, 2012 A. Möller, S. Diewald, L. Roalter, M. Kranz 6
  7. 7. Distributed Multimodal Information Processing Group Technische Universität MünchenExcursus: Pointing (Vision-based Recognition)•  Image processing is used to detect visual features of an image•  A query in feature space returns similar images from a reference database•  Good choice of feature type allows very reliable results (e.g. MSER) –  High distinctiveness (e.g. by using text-related features) –  Scale invariance (works at different distances) –  Rotation invariance (works at different angles)•  Enabled by rise in mobile CPU performance (multi-core...)Oct 15, 2012 A. Möller, S. Diewald, L. Roalter, M. Kranz 7
  8. 8. Distributed Multimodal Information Processing Group Technische Universität MünchenPrototype•  Implementation as Android application•  47,000 drugs in query database•  100,000 reference imagesOct 15, 2012 A. Möller, S. Diewald, L. Roalter, M. Kranz 8
  9. 9. Distributed Multimodal Information Processing Group Technische Universität MünchenOutline Background and Motivation Scenario and Prototype User Study Discussion and ConclusionOct 15, 2012 A. Möller, S. Diewald, L. Roalter, M. Kranz 9
  10. 10. Distributed Multimodal Information Processing Group Technische Universität MünchenResearch Questions•  RQ1: What advantages and disadvantages of identification techniques, as presented in MobiMed, can be determined? –  ...in terms of effectiveness? large-scale, online –  ...in terms of efficiency? lab•  RQ2: Which method is preferred by users? –  ...a priori? large-scale, online –  ...after practical use? lab•  RQ3: What potential do people see for MobiMed as a whole? –  ...a priori? large-scale, online –  ...after practical use? labOct 15, 2012 A. Möller, S. Diewald, L. Roalter, M. Kranz 10
  11. 11. Distributed Multimodal Information Processing Group Technische Universität MünchenMethodology•  Online study –  Human Intelligence Task at Amazon mTurk –  149 participants •  74 females, 75 males •  17-79 years (average: 31, standard deviation: 11) –  Questionnaire survey•  Lab study –  16 participants •  6 females, 10 males •  22-69 years (average: 31, standard deviation: 12) –  Experimental task + Questionnaire survey •  Identification of 10 packages with each of four methods •  Within-subjects design, permuted orderOct 15, 2012 A. Möller, S. Diewald, L. Roalter, M. Kranz 11
  12. 12. Distributed Multimodal Information Processing Group Technische Universität MünchenResults: RQ1 (Individual Method Comparison)Method Advantages DisadvantagesScanning Quick, precise, high Visual code + camera familiarity required, need to find and focus on codeTouching Hassle-free, fool-proof, NFC augmentation and quick NFC-capable phone required, privacy skepticismPointing Intuitive to use, „most Computational demand, human form“ of interaction, ambiguous results possible works from any angle, works also with catalog/website images, no product tagging requiredText Highest familiarity, accurate, High amount of typing, search term flexibility misspelling, slow, difficultOct 15, 2012 A. Möller, S. Diewald, L. Roalter, M. Kranz 12
  13. 13. Distributed Multimodal Information Processing Group Technische Universität MünchenResults: RQ1 (Efficiency)Oct 15, 2012 A. Möller, S. Diewald, L. Roalter, M. Kranz 13
  14. 14. Distributed Multimodal Information Processing Group Technische Universität MünchenResults: RQ2 (User Preferences) -3 = strongly disagree, +3 =strongly agreeObservations/interpretations:•  Touching was only #3 in online survey, but rated best in lab study•  Possible explanation: low familiarity (as soon as people used it, they liked it)Oct 15, 2012 A. Möller, S. Diewald, L. Roalter, M. Kranz 14
  15. 15. Distributed Multimodal Information Processing Group Technische Universität MünchenResults: RQ3 (Utility of Tool in Scenario)•  Information sources on drugs: •  Suggestions for additional –  Doctor/pharmacist (75%) features –  Package insert (69%) –  Price comparison –  Books/internet (56%) –  Active ingredient analysis –  Self-diagnose•  Would you be interested in –  Personalized medication MobiMed as alternative source for management drug information? 88%•  Would you use a system such as MobiMed? 82%•  Average amount of money subjects would spend: $8.40 (aged >25: $14.01)Oct 15, 2012 A. Möller, S. Diewald, L. Roalter, M. Kranz 15
  16. 16. Distributed Multimodal Information Processing Group Technische Universität MünchenResults: RQ3 (Usability of Prototype)Oct 15, 2012 A. Möller, S. Diewald, L. Roalter, M. Kranz 16
  17. 17. Distributed Multimodal Information Processing Group Technische Universität MünchenOutline Background and Motivation Scenario and Prototype User Study Discussion and ConclusionOct 15, 2012 A. Möller, S. Diewald, L. Roalter, M. Kranz 17
  18. 18. Distributed Multimodal Information Processing Group Technische Universität MünchenDiscussion and Conclusion•  Physical Mobile Interaction is popular and efficient –  Was preferred over conventional (text) search –  Was faster than text search•  Touching and Scanning evaluated best –  Fastest and most popular physical mobile interaction methods –  Touching faster and more popular than scanning in lab study –  Scanning more popular in online survey (familiarity)•  Vision-based Search (pointing) as future alternative? –  Natural; works for any object (no augmentation needed) –  Reliability/speed improvement needed, but almost as fast as scanning•  Best method depends on intended scenario•  General demand for medical appsOct 15, 2012 A. Möller, S. Diewald, L. Roalter, M. Kranz 18
  19. 19. Distributed Multimodal Information Processing Group Technische Universität München Thank you for your attention! Questions? ? ? andreas.moeller@tum.de www.vmi.ei.tum.de/team/andreas-moeller.htmlOct 15, 2012 A. Möller, S. Diewald, L. Roalter, M. Kranz 19
  20. 20. Distributed Multimodal Information Processing Group Technische Universität MünchenReferences•  Slide 3: –  Rukzio, E. Physical mobile interactions: Mobile devices as pervasive mediators for interactions with the real world. PhD thesis, 2006 –  Want, R., Fishkin, K., Gujar, A., and Harrison, B. Bridging physical and virtual worlds with electronic tags. In Proceedings of the SIGCHI conference on Human factors in computing systems: the CHI is the limit, ACM (1999), 370–377.•  Slide 10: https://www.mturk.com/mturk/welcome•  All other images: Microsoft ClipArt 2012Oct 15, 2012 A. Möller, S. Diewald, L. Roalter, M. Kranz 20
  21. 21. Distributed Multimodal Information Processing Group Technische Universität MünchenPaper Reference•  Please find the associated paper at: http://dx.doi.org/10.1145/2399016.2399022•  Please cite this work as follows:•  Andreas Möller, Stefan Diewald, Luis Roalter, and Matthias Kranz. 2012. MobiMed: comparing object identification techniques on smartphones. In Proceedings of the 7th Nordic Conference on Human-Computer Interaction: Making Sense Through Design (NordiCHI 12). ACM, New York, NY, USA, 31-40. DOI=10.1145/2399016.2399022 http://doi.acm.org/ 10.1145/2399016.2399022Oct 15, 2012 A. Möller, S. Diewald, L. Roalter, M. Kranz 21
  22. 22. Distributed Multimodal Information Processing Group Technische Universität MünchenIf you use BibTex, please use the following entryto cite this work: @inproceedings{Moller:2012:MCO:2399016.2399022, author = {M"{o}ller, Andreas and Diewald, Stefan and Roalter, Luis and Kranz, Matthias}, title = {MobiMed: comparing object identification techniques on smartphones}, booktitle = {Proceedings of the 7th Nordic Conference on Human-Computer Interaction: Making Sense Through Design}, series = {NordiCHI 12}, year = {2012}, isbn = {978-1-4503-1482-4}, location = {Copenhagen, Denmark}, pages = {31--40}, numpages = {10}, url = {http://doi.acm.org/10.1145/2399016.2399022}, doi = {10.1145/2399016.2399022}, acmid = {2399022}, publisher = {ACM}, address = {New York, NY, USA}, keywords = {object identification, physical mobile interaction, pointing, scanning, touching}, }Oct 15, 2012 A. Möller, S. Diewald, L. Roalter, M. Kranz 22

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