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CS260: Research Topics in HCI Fall 2006

CS260: Research Topics in HCI Fall 2006. John Canny UCB EECS. The Course. CS260 this semester is a focused overview of current research in HCI. The focus is set by the students taking it. There will be at least one class presentation by each student, based on their area of interest.

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CS260: Research Topics in HCI Fall 2006

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  1. CS260: Research Topics in HCI Fall 2006 John Canny UCB EECS

  2. The Course • CS260 this semester is a focused overview of current research in HCI. The focus is set by the students taking it. • There will be at least one class presentation by each student, based on their area of interest. • There is also a semester-long class project, either individual or pair.

  3. Sample Projects:Tactile Feedback in Music Applications Kerry Kimes

  4. Sample Projects:Usability analysis of UC-WISE +

  5. MISS - Multiple-Interface Scheduling System CS260, Spring 2002 Juha Johansson February 28

  6. User Study for Designer’s OutpostKatie Everitt

  7. Sample Projects: Privacy Management in Ubiquitous Computing Xiaodong Jiang Scott Lederer February 28, 2002

  8. CS260 Project Checkpoint Livenotes: Second Iteration of UI Matthew Kam Orna Tarshish

  9. ObjDraw – A tool for use in CS61a at Berkeley Project Checkpoint Ryan Stejskal Feb. 28, 2002 Create a new tool that allows students to explore one of the hardest “big ideas” – object-oriented programming – outside of class time Similar to an existing tool, “envdraw” A graphical interface to object-oriented programming as implemented in 61a

  10. Sound Visualization for the Hearing-Impaired Wai-ling Ho Ching • Convenient, low cost home audiometry is desirable and implementable with the power of current home computers • Pure tones of varying frequencies and degrees of loudness are played to each ear to determine range and degree of hearing loss

  11. Source Code Visualization Zachary Weinberg • Decades of history, thousands of modifications • No easy way to find the changes you care about • Poor collective memories

  12. HCI: the state of the union • Ideas appeared in special issue of Queue Magazine on HCI (JFC guest editor). • Outline: brief recent history of modern HCI • Why things are different • What it means for interactive system design

  13. Modern HCI • We can define modern HCI as the iterative, user-centered design of systems. • There are two key data points in this evolution, the Xerox Alto and the Xerox Star. • They represent two very different approaches to design, and two very different outcomes.

  14. Xerox Alto • Began in1970, soon after PARC formed. Design team: Alan Kay, Chuck Thacker, Butler Lampson • Real target was a laptop (dynabook), but a personal computer was the closest you could achieve in the 1970s. • Features: • Mouse • Overlapping windows • Ethernet • But • Still “mostly text” UI • Lacked a killer app

  15. Xerox Star • Very different pedigree. Not a research prototype. • Created by Xerox’s product division (Don Masarro). • Goal was to support generic office work. • Project leader David Liddle tappedexperts from PARC to help with Star’sdesign process. • Started with a “best practice” designdocument: • Scenarios • Task analysis • Conceptual modeling • Rapid prototyping

  16. Xerox Star • The Star’s design process is completely modern: it’s a perfectly good example of best practice today. • The result was a completely modern UI design (a WIMP interface). • Liddle stated that the Star was a “big improvement on its successors” • It’s a fair statement. Star’s UI wascopied in Macs and later PCs. • Its object-oriented design wascleaner than the leading OSes decades later.

  17. Design process • Neither machine succeeded in the marketplace, although the Star’s design is arguably the most influential of any machine on today’s UIs. • They represent two different design processes: • Visionary, techno-centric (and theory-centric) design, embodied in the Alto. • User-centric, market-driven, evolutionary design, embodied in the Star.

  18. Where we are: • Desktop PCs are primarily office (knowledge work) machines. • The IT market is much broader now. Intel’s Taxonomy • Office • Mobile • Health • Home (+ emerging regions?) • The last 3 are different environments, top-to-bottom. The hardware is different too: In mobile we have cell phones, PDAs, cameras, GPSes, portable games, iPods etc. The Health and Home market’s seem to be still in flux.

  19. Where we are: • Looking again at the new markets: • Mobile • Health • Home • There are many differences in how people access information: • Many more short episodes • More proactivity (reminders, alerts, automation etc.) • More interaction between “device” and “world” • Scarcity of a “desktop” with keyboard, screen, mouse • Increased role of context: where, when, who, history,…

  20. Where we are: • HCI has mostly followed an evolutionary strategy: its target (the knowledge work environment) has stayed the same for most of its history. • We’re currently in a “disruptive period” where evolution gives way to revolution.

  21. Technology themes: Perceptual interfaces (vision, speech, sensing) Context modeling

  22. Technology themes: • Perceptual Interfaces: Translate sensed data into relevant (system) actions for the user’s task/activity. Sensing is everywhere in new IT domains (cameraphones, occupancy sensors). • Context: Is what is “understood” by humans when they interact with each other, and makes efficient communication possible. Very important for emerging IT domains like mobile and home. Each supports the other.

  23. Context: • Traditional HCI definition (Abowd et al.): • Place and time • User preferences • User activity (task) • Most of the papers on context focus on what data to use, not on what to do with it. • Alternative notion: Context comprises • User activity (what is it, and user’s role?) • Situation (social convention, what would a stranger do?) • This allows us to assign meaning to observations: • What are the anticipated consequences of the observations?

  24. Perceptual Interfaces: • Perceptual Interfaces (like computer vision and speech) have fared poorly in knowledge work environments. Why? • They are doing much better in the new domains. • E.g. the largest market for speech software now appears to be health care. • But new environments are physically challenging: noisy, erratic lighting etc. • But these environments are also context-rich (not true for the office).

  25. Today’s mobile phone 200 mips This year’s Smartphone (free with service contract) • 150-200 MHz ARM processor • 32 MB ram • 2 GB flash (not included) Windows-98 PC that boots quickly! Plus: • Camera • AGPS (Qualcomm/Snaptrack) • DSP cores, OpenGL GPU • EV-DO (300 kb/s), Bluetooth

  26. Context-Aware Face Recognition

  27. Perceptual Interfaces - Vision Cameraphones are capable serious computer vision now. Right now, the vision algorithms available include: • Motion • Barcodes • OCR text (business cards etc.) Technically feasible: • Face recognition • Building or streetscape recognition

  28. Context-Aware Face Recognition • Face recognition alone - 43% accurate(state of the art computer vision) • Context analysis alone - 50% accurate(Face prediction from contextual data on the phone) • Context+Content analysis - 60% accurate Figure 1. (Top) Subjects with frontal pose, (Bottom) Same

  29. Context-Aware Place Recognition • Image analysis alone - 30% accurate • Context analysis alone - 55% accurate • Context+Content analysis - 67% accurate

  30. Photo Share Guesser 0.8 0.7 0.6 0.5 SFA prediction 0.4 Baseline 0.3 0.2 0.1 1 2 3 4 5 6 7 8 9 10

  31. Perceptual Interfaces - Vision TinyMotion is a software mouse for cameraphones. By moving the camera against any background, real-time image motion estimation provides mouse coordinates.Also great for games

  32. Perceptual Interfaces - Speech Speech recognition technology has improved steadily in the last ten years, particularly in noisy environments. Speech was never a good match for office environments. But the mobile playing field is completely different. Mobile users often need their eyes and hands free, and the phone will always have a voice channel for telephony.

  33. Speech on Mobile Phones Restricted speech recognition is available on many phones. Large-vocabulary recognition just appeared on cell phones last year (Samsung P207). Its a huge step. It enables the next generation of mobile speech-based apps: • Message dictation • Web search • Address/business lookup • Natural command forms(no need to learn them)… Most of this technology was developed in the US by VoiceSignal Technologies.

  34. Speech for Developing Regions Speech is an even more important tool in developing regions. Literacy is low, and iconic (GUI) interfaces can be hard to use. Unfortunately, IT cannot help most of these people because they lack even more basic skills – fluency in a widely-spoken language like English or Mandarin. This project focuses on teaching English in an ecologically appropriate way. Speech-based phones are ideal for this.

  35. Speech for Developing Regions Speech (with headset) allows students to learn while working. It leaves their eyes and hands free, and engages their minds during tedious, manual work. Some game motifs: • Safari: hear sound & say the name in English • Karoake: in English • Listen and summarize: BBC, cricket etc. • Treasure hunt: leave LB clues in English • Adventure games: dialog-driven scenarios

  36. Context-Awareness Context-awareness is the holy grail for next generation mobile applications: • Location (e.g., video store, kitchen) heavily shapesthe user’s likely actions. So does time,place, identity of friends, etc. • These data are often inferred byperceptual systems. • But when people say “context” theymean much more: con-text is literallywith-the-text; its all the other informationneeded to make sense of a text (or a user interface action).

  37. Making more of context… There is an enormous amount of social sciences that points to two sources of high-level context: • Activity: based on subject’s personal history and what they are engaged in. • Situation: a set of socially-understood normed environments and behaviors within them. • In both cases there is a structure of • People (and their roles) • Objects • Actions or scripts

  38. Making more of context… There is an enormous amount of social sciences that points to two sources of high-level context: • Activity: based on subject’s personal history and what they are engaged in. • Situation: a set of socially-understood normed environments and behaviors within them. • In both cases there is a structure of • People (and their roles) • Objects (and their genres) • Actions or scripts

  39. Making more of context… Dealing with context is a great challenge because it covers so many fields, from sociology and linguistics to machine learning. But the potential payoffs are great as well… E.g. JCR Licklider’s OLIVER (Online Vicarious Expediter and Responder)

  40. Summary We are at a fork in the road in HCI. We face a new playing field (app. Domains) with new demands. We have an opportunity (and probably a necessity) to build systems that are much more context-aware. Future systems can also leverage machine perception to build and exploit context. The net result is systems that understand (and respond to) us much better.

  41. Next time… I propose to start on learning systems for Wednesday. I can cover the lecture. I’d like a volunteer for Monday’s lecture.

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