T Marjaana Träskbäck Design Principles for Intelligent Environments Coen M. H., AAAI-98 Introduction Intelligent Room Room Vision System Speech Interaction Conclusion

T Marjaana Träskbäck Introduction Intelligent environment (IE) –Highly embedded, interactive spaces –used to enhace ordinary activity seamlessly Goal –computers to participate in new activities –HCI via gesture, voice, movement, and context Presents Intelligent Room prototype space –research question: How IEs should be designed?

T Marjaana Träskbäck Intelligent Room Spaces in which computation is seamlessly used to enhance ordinary activity The UI primitives of these systems are not menus, mice and windows, but gestures, speech, affect, and context IEs are both embedded and multimodal and thereby allow people to interact with them in natural ways

T Marjaana Träskbäck Intelligent Room Rather than to make computer-interfaces for people, we want to make people-interfaces for computers Enable tasks historically connecting computers to phenomena

T Marjaana Träskbäck Why this isn’t Ubiquitous Computing? They need many connections with the real world IE advocate minimal hardware modifications and ”decorations”

T Marjaana Träskbäck Intelligent Room Half of the room is a conference room The other half has room for computation

T Marjaana Träskbäck Intelligent Room Problem1: Computer vision and speech recognition/understanding system development Problem2: Interconnecting all of the rooms many subsystems and coordinating the flows of information –> Scatterbrain (Coen M. Building Brains for Rooms: Designing Distributed Software Agents)

T Marjaana Träskbäck Room Vision Systems Tracking system –2 wall mounted cameras –3 steerable cameras to get optimal view Pointing –two overhead LCD projectors which support finger and laser pointing interactions –Finger pointing: wo parallel cameras –Laser pointing: othogonal camera

T Marjaana Träskbäck Room Vision Systems Interactive table –room detects hand-pointing gestures not very natural form of communication –newly placed documents –post-it notes assigned to lights etc.

T Marjaana Träskbäck Room Vision Systems Solutions –robust vision systems that require little calibrations and are self-training Embedded the room’s vision systems to reinforce one another Agents (lighting, drapes etc.) communicate with it before changing anything In tracking most data is irrelevant; important is where someone is when she stops moving or ehwn she crossed a particular threshold

T Marjaana Träskbäck Speech Interaction Should support spoken language interactions –people wear wireless lapel microfones –wakes up the computer by saying ”computer” –hands- and eyes-free stly of interaction –unimodal –the computer can address the user

T Marjaana Träskbäck Room Vision Systems Issues –The tracking network need to be trained –The system is sensitive to any deviation from its training conditions –Computer vision system that rely on background segmentation, can be extraordinarily sensitive to environmental lighting conditions Shadows are particularly difficult

T Marjaana Träskbäck Speech Interaction issues –The size of the recognition grammar divided into subsets –Current context is taken into account other systems can help to overcome comptational limitations –Can help other modalities

T Marjaana Träskbäck Conclusions IEs need to be more than mix on systems Communication among modalities can lead –to synergistic reinforcement –to a more reliable system Modalities need to carefully selected –easy to install –easy to maintain –able to be used under different environmental conditions IEs success: self-training and avoiding manual calibration!