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Explore the integration of contextual zoom and pliable display technology in a learning system interface, enhancing user experience. Features focal regions, compression regions, and undistorted contexts for efficient data visualization.
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Pliable Display Technology: Contextual Zoom as a Learning System Interface Joshua R. New Special Topics Jacksonville State University
Outline • Med-LIFE • Pliable Display Technology • Contextual Zoom • Learning System Features
Med-LIFE Fuse
Med-LIFE Explore
Med-LIFE Learn
Pliable Display Technology • Screen Real Estate Problem • Ubiquitous problem in that computers can store and manipulate vast amounts of information but has a comparatively small screen on which this data can be viewed
Pliable Display Technology • Sheelagh Carpendale (PhD thesis) – Elastic Presentation Space (http://pages.cpsc.ucalgary.ca/~sheelagh) • IDELIX – Pliable Display Technology (www.idelix.com) • PDT3D SDK, Beta Tester • C++, system-independent, interfaces with several other libraries such as OpenGL, QT, etc.
Contextual Zoom Three parts • Focal Region (Magnified region) – Different shapes (circle, square, etc.) • Shoulder (Compression region) – Different compressions • Context (Undistorted image)
Original Image 3D Image User’s View Contextual Zoom • Example of contextual zoom • Extends 2D image data into 3D for zooming of the focal region and compression of image data in the shoulder region
Contextual Zoom • Shoulder – example of different drop-off functions for image compression in the shoulder region
Contextual Zoom • Must alter position of lens so that data always points toward user instead of simply upward
Contextual Zoom • PDT3D SDK allows the use of an efficient and intuitive lens control interface
Learning System Features Allows: • Addition/deletion of lenses • Interaction with a contextual zoom lens • Hiding/unhiding of a lens • Wireframe mode – see how image is being mapped • Fast mode – less accurate, but better for slow computers • Marking of examples and counterexamples • Undo feature to remove last mark • Transparency changes for the marks and the texture independently
Future Directions • Integration with Med-LIFE Learning tab • Integration with Artificial Intelligence SFAM system For additional information, please visithttp://ksl.jsu.edu.