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Designed to Fit Challenges of Interaction Design for Clothes Fitting Room Technologies Bo Begole , parc Takashi Matsumoto , Keio University Wei Zhang , Oregon State University Nicholas Yee , parc Juan Liu , parc Maurice Chu , parc HCI International, July 2009

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Implicit Interaction <ul><li>Conventional systems: User initiates interaction and drives the system </li></ul><ul><li>Implicit Interaction : System perceives state of user and situation and acts on users’ inferred goals </li></ul><ul><ul><li>Simplifies user experience </li></ul></ul><ul><ul><li>Little or no training required </li></ul></ul>Responsive Mirror Responsive Technologies Information Recommendation Clothing Recognition Psychographic Profiling [ ICDSC 2008 ] [ IUI 2008, HCII 2009 ] [ CHI 2008 ] Magitti Related PARC Research: also: Human-Robot Interaction Multi-party conversations Camera-based tracking MIT Media Lab Xbox Natal

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Clothes Shopping as an Information Seeking Activity Browse Filter Evaluate Decide, Buy Availability, cost, size, colors, texture, feel, fit, style trends, etc. In-Store Online

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Related Work Apparel Fitting Technologies <ul><li>Virtual fitting technologies </li></ul><ul><ul><li>Project image of clothing on image of shopper or 3D model </li></ul></ul><ul><ul><li>Helps pre-filter but ultimately clothing must be tried on </li></ul></ul><ul><li>Fitting room technologies </li></ul><ul><ul><li>Detect clothing items and retrieve information – price, colors, in stock </li></ul></ul><ul><ul><li>Record videos of fitting </li></ul></ul><ul><ul><li>Send to friends for comments </li></ul></ul><ul><ul><li>Project virtual clothing on mirror </li></ul></ul><ul><ul><li>Don’t provide access to prior trials </li></ul></ul><ul><ul><li>Don’t show social context of fashion </li></ul></ul>

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Responsive Mirror Implicitly controlled vision-based system providing information for “self” comparison and “social” context The Future of … Dressing Rooms , BNet, Sumi Das video (min1:25-2:02)

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Privacy Considerations <ul><li>What are the implications of introducing a camera to this semi-private setting? </li></ul><ul><li>Altman’s three boundaries </li></ul><ul><ul><li>Disclosure – clothes fittings are typically only shared with co-present shoppers, friends, family </li></ul></ul><ul><ul><li>Identity – Apparel trials are a time when a person is experimenting with their “presentation of self” </li></ul></ul><ul><ul><li>Temporal – fitting sessions are usually ephemeral, not preserved for future scrutiny </li></ul></ul><ul><li>Social aspects </li></ul><ul><ul><li>What image do I project when wearing these clothes? </li></ul></ul><ul><ul><li>What do other people who wear these clothes look like? </li></ul></ul>

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Formative Study <ul><li>Quick examination of privacy concerns </li></ul><ul><li>Participants </li></ul><ul><ul><li>12 males, 28-52 years </li></ul></ul><ul><ul><ul><li>Limited population </li></ul></ul></ul><ul><ul><ul><li>Clothes matching algorithm only worked on men’s shirts </li></ul></ul></ul><ul><li>Within subjects analysis </li></ul><ul><li>Three Conditions </li></ul><ul><ul><li>Mirror alone </li></ul></ul><ul><ul><li>Mirror with Previous Outfit </li></ul></ul><ul><ul><li>Mirror with Other people in similar outfits </li></ul></ul><ul><li>Task </li></ul><ul><ul><li>Select one out of 6 shirts for each condition (18 shirts total) </li></ul></ul>

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Results - Overall <ul><li>Buying decisions were not different across conditions </li></ul><ul><ul><li>The characteristics of the clothing mattered more than the technology </li></ul></ul><ul><li>Which condition did you prefer? (1=highest, 5=lowest) </li></ul><ul><ul><li>Previous Outfit plus Other People (M = 1.92) (not experienced) </li></ul></ul><ul><ul><li>Previous Outfit (M = 2.00) </li></ul></ul><ul><ul><li>Other People (M = 2.83) </li></ul></ul><ul><ul><li>Plain Mirror (M = 3.25) (  2 = 9.10, p = .03) </li></ul></ul><ul><li>Which condition was more helpful? </li></ul><ul><ul><li>Previous Outfit (M = 3.00) </li></ul></ul><ul><ul><li>Other People (M = 2.5) </li></ul></ul>

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Results - Disclosure <ul><li>How bothered by people in the following groups seeing images from the fittings? </li></ul><ul><ul><li>(5=bothers me a great deal, 1=doesn’t bother me at all) </li></ul></ul><ul><ul><li>Family (M=1.08) </li></ul></ul><ul><ul><li>Friends (M=1.50) </li></ul></ul><ul><ul><li>Stranger (M=2.08) </li></ul></ul><ul><ul><li>Co-worker (M=2.25) </li></ul></ul><ul><ul><li>No significant effect regarding gender </li></ul></ul><ul><ul><li>Level of concern was significantly higher for bad shirts (M=3.0) versus good shirts (M=1.42) (p = .001) </li></ul></ul><ul><li>Implication: Access control at just two levels: </li></ul><ul><ul><li>Friends and Family </li></ul></ul><ul><ul><li>Co-workers and Strangers </li></ul></ul>not sig. diff’t not sig. diff’t sig. diff’t

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Results - Identity <ul><li>How often do you think about </li></ul><ul><ul><li>(5=Always, Often, Sometimes, Seldom, Never=1) </li></ul></ul><ul><ul><li>Someone you know who might like these clothes (M=2.67, SD=0.98) </li></ul></ul><ul><ul><li>How similar to what other people you know are wearing (M=2.92, SD=0.9) </li></ul></ul><ul><ul><li>How similar to what other people you don’t know are wearing (M=2.33, SD=0.98) </li></ul></ul><ul><li>Implication: Providing information on what other people are wearing would be useful sometimes </li></ul>

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Results – Temporality <ul><li>Would you want to remove images in the future if your tastes change? (5=Definitely, 1=Definitely Not) </li></ul><ul><ul><li>(M=3.08, SD=1.16) (closest to Possibly) </li></ul></ul><ul><li>Preferred periods of time </li></ul><ul><ul><li>within 3 months (5 participants) </li></ul></ul><ul><ul><li>within 1 year (5 participants) </li></ul></ul><ul><ul><li>never (2 participants) </li></ul></ul><ul><li>Implication: systems can remind users at 3 month and 1 year period to review their image record </li></ul>

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Summary & Conclusions <ul><li>Physical apparel shopping requires different information than online shopping </li></ul><ul><ul><li>Apparel fit, feel, drape, texture, translucency, etc. </li></ul></ul><ul><li>Privacy is a concern but not a block </li></ul><ul><ul><li>understanding user concerns in Altman’s three boundaries can help system designers </li></ul></ul><ul><li>Future Directions </li></ul><ul><ul><li>Countertop version for eyeglasses, jewelry, hats, makeup, hair, … </li></ul></ul><ul><ul><li>Front-camera tracking algorithms </li></ul></ul><ul><ul><li>Adding sales support to the system </li></ul></ul><ul><li>Contacts welcome! </li></ul><ul><ul><li>[email_address] </li></ul></ul>Counter-top Responsive Mirror

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The end

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In-Store vs. Online Goal: Bring the best of both worlds together Pros Cons In-Store Browse/ Select Touch and feel clothing Limited to in-store inventory Evaluate Can evaluate tactile fit and visual style, Real-time feedback Comparisons conducted sequentially, Feedback limited to co-present friends Online Browse/ Select Huge selection of clothing Only visual look of clothing Evaluate Can compare multiple clothing simultaneously, Feedback from large number of people Can only evaluate visual style, No real-time feedback from friends