Lab Seminar

Lab Seminar2014-11-21@UVRLabSung Sil Kimmania@kaist.ac.kr

Progress report 1ContentsProgress and PlansPaper Review2HRHRP Goals , UI . / , . .

HRHRP 3ProgressCHI15 Face Recognition via Person-Specific Facial Expression Acquired By Intended Inconvenient Interface HRHRP

HCI korea CHI . system 4CHI15 Review 1Primary reviewers comment:A very interesting idea with good potentialHOWEVER, has too severe flaws: both user studies do not seem to be strong enough and (algorithm) does not present a strong contributionI recommend the authors to re-do the user studies with a stronger design and make the paper much stronger, and re-submit. I do not believe a rebuttal can change the reviewers opinions in this case.5CHI15 Review 2External reviewers comment:a novel interesting idea to face recognition, cause most of previous works target on learning expression invariant face representations for face recognitionHowever, the technical approach, is not new and a generic one not specific to smiling faces.The variation of facial expressions is a relatively easy factor in face recognition. Aging, face pose, and the uneven lighting variations (e.g., shadow), are considered more challenging issues.Overall, the paper presents an interesting idea to face recognition, however, the technical approach is not new and a generic one6CHI15 Review 3External reviewers comment:none of the three parts are conclusivethe idea is really innovative and it would be super interesting to know what might happen if you need to smile towards your computer (phone, etc.) everyday. However as the paper is written it contains many flaws and weaknessesthe experiment is to small to draw any major conclusionsbreak this work into different parts and focus on the key contributions for each parts7CHI15 Review 4External reviewers comment:novelty of the work is very lowwork was tested on 6 subjects onlyOne of the fundamental questions that should be answered is concerned with the persistence and individuality of facial identity patterns in either static domain or dynamic domain. The paper failed to address this issue and the technique used for FR is not well justified as to why it is the best choice for person identification with smiley face images. The usability study of the system needs be expanded

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9Ongoing progressUndergraduate Research Program (URP)http://kchannel.kaist.ac.kr/CH751-000, 2-3 people per team 2014 11 26 () Mobile HCI15http://mobilehci.acm.org/2015/Aug 24-27th, 2015Submission for paper: Feb 6th, 2015

: urp :

10Mobile HCI: Mobile device / 1) personal data 2) self-reflection /: functionality application teste qualitative survey .: / () personal data quantified self/ ( business model )11Mobile HCI14Suggested Topics:Novel user interfaces and interaction techniques / Mobile social networks / Context-aware systems/ Multimodal interaction (including audio and speech) / User-centred design tools and methods for mobile systems / Ethnographical and field studies with mobile technology / Group interaction and mobility communities / Services for mobile devices / The design of location-based services for mobile devices / The design; evaluation and case studies-of-use of application development environments / Wearable computing, smart clothes, new devices and sensors / Mobile entertainment, storytelling and location based gaming / Aesthetic interaction and experience design / Affective Computing and modelling of the environment / Personal assistance with mobile devices / Mobile art / Mobility and work environments / Evaluation and usability of mobile devices and services / Mobile accessibility / Model-based design of interactive mobile systems / Visualization techniques for the mobile context (including 3D graphics on mobile devices) / Safety issues e.g., in-car user interfaces, payments / Trust, privacy, content protection, legal aspects & issues in mobile application & services

Mobile hci 12Mobile HCI14ProceedingsSocial Network & Input and Interaction Devices and Interaction DesignContext Awareness3DE-LearningGesture InteractionUser-Centered DesignInput and InteractionGesture & Text-EntryRecommender Systems and CSCW

proceedings topic.

(mobile) HCI input, interaction 13Slide to X: Unlocking the Potential of Smartphone UnlockingCHI14University of TorontoSession: Crowdsourcing

14AbstractIn this paper, we explore how replacing the regular unlock screen with one that asks the user to perform a simple, optional task, can benefit a wealth of application domains, including data collection, personal-health metrics collection, and human intelligence taskswe show that people are willing to perform microtasks presented through this interface and continue to do so throughout the day while they visit different locations as part of their daily routines.We then discuss how to implement this concept and demonstrate three applications.15Video

flavored chipsWheelchair friendly? survey16ContributionsThe use of micro-tasks as a replacement for traditional phone unlocking.A study of regular unlocking patterns and of users willingness to perform micro-tasks in that context.A set of three example applications which demonstrate the Slide to X concept.17Experiment10 participants, age 19-23Android 2.3 or higherFunctionalitiesPosition data collection: records users geospatial location every 10 min Usage data collection: records time and location whenever the screen is unlockedSlide to X functionality: presents one of several unlock screens1)traditional android unlock screen2)simple mathematical question3)introspective questions about health

how happy have you felt in the past hour in the last hour, have you had any coffee 18

Slide to X interface

19Application 1

20Application 2

Have you eaten yetAre you happy right nowHealthcare professional monitoring

21Application 3

Amazon mechanical turk business model that utilizes human intelligence tasks task crowd marketplace

best among several photographs of a storefront, writing product descriptions, or identifying performers on music CDs22Figure 2

23ResultIn total,16,398 screens unlocks occured8,118 questions posed8,280 simple unlock screen displayed8 of 10 participants - frequency of questions reasonable7 of 10 participants wanted more variant questions with less frequencySlideToCure application can raise approximately $6,864,000 per day

24Things learnedSlide To QuantifySelf can be improvedUsing (unobtrusive) face recognition and facial expression detectionStress management is equivalent to smile inducementUsers willingness (to use the service) is critical

25Questions?https://sites.google.com/site/uvrlab2014/mania@kaist.ac.kr