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FLEXPAD:HIGHLY FLEXIBLE BENDING INTERACTIONS FOR PROJECTED HANDHELD DISPLAYS

JOURNAL:ACM, NEW YORK AUTHORS:JURGEN STEIMLE, ANDREAS JORDT, PATTIE MAES Presented by Aiswarya Gopal (P2ELT13002) Athira.L (P2ELT13023). FLEXPAD:HIGHLY FLEXIBLE BENDING INTERACTIONS FOR PROJECTED HANDHELD DISPLAYS. WHAT IS FLEXPAD…???.

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FLEXPAD:HIGHLY FLEXIBLE BENDING INTERACTIONS FOR PROJECTED HANDHELD DISPLAYS

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  1. JOURNAL:ACM, NEW YORK AUTHORS:JURGEN STEIMLE, ANDREAS JORDT, PATTIE MAES Presented by AiswaryaGopal(P2ELT13002) Athira.L(P2ELT13023) FLEXPAD:HIGHLY FLEXIBLE BENDING INTERACTIONS FOR PROJECTED HANDHELD DISPLAYS

  2. WHAT IS FLEXPAD…??? • Interactive system having a depth camera, projector, plain paper and hand-held displays

  3. ABSTRACT • Track deformed surfaces from depth images • Capture complex deformations and provide fine details • Prevents occlusions from fingers and hands • Avoids use of markers

  4. INTRODUCTION • Manipulation of real world objects for interaction with computer systems • Integration of physical and digital information • Depth sensors • Degree o freedom • People bend pages in book • Bending interaction

  5. CONTD… • Two main contributions • Algorithm for capture of complex deformations • Detection of hands and fingers • Evaluation • Two evaluation studies

  6. RELATED WORK • Deformation capturing • Technologies used • Light Space • Kinect Fusion • Omni touch • Proxy particles • Disadvantages

  7. CONTD…. • Flexible Display Interfaces • Two types of work • Deformable sheet or tape • Deformation of handheld displays

  8. FLEXPAD OVERVIEW • Components used • Kinect camera • Projector • Sheet of paper • Foam or acrylic • Flexible display material • Any sheet can be used as passive display • Two materials of sheet

  9. FLEXPAD IMPLEMENTATION • Kinect depth sensors • Looks at • Removal of hands and fingers • Global deformation model • How global deformation model

  10. OPTICAL SURFACE MATERIAL ANALYSIS FOR HAND AND FINGER DETECTION Figure 3: Detection of skin by analyzing the point pattern in the Kinect infrared image. Center: Input. Right: Classification

  11. Figure 4: Dimensions of the deformation model (left) and examples of deformations it can express (right). Figure 4: Dimensions of the deformation model (left) and examples of deformations it can express (right). Figure 4: Dimensions of the deformation model (left) and examples of deformations it can express (right). Figure 4: Dimensions of the deformation model (left) and examples of deformations it can express (right). Figure 4: Dimensions of the deformation model (left) and examples of deformations it can express (right). Figure 4: Dimensions of the deformation model (left) and examples of deformations it can express (right). Figure 4: Dimensions of the deformation model (left) and examples of deformations it can express (right). MODELING THE DEFORMABLE SURFACE

  12. LIMITATIONS • Trap deformations directly observed directly from Kinect sensors • Trade-off between tracking stability and set of detectable deformations

  13. APPLICATIONS • High flexibility • 1:1 mapping

  14. Figure 5: Exploring curved cross-sections (a), flattening the view (b), comparing contents across layers (c) Figure 5: Exploring curved cross-sections (a), flattening the view (b), comparing contents across layers (c) Figure 5: Exploring curved cross-sections (a), flattening the view (b), comparing contents across layers (c) Figure 5: Exploring curved cross-sections (a), flattening the view (b), comparing contents across layers (c) EXPLORING AND ANALYZING VOLUMETRIC DATASETS

  15. ANIMATING VIRTUAL PAPER CHARACTERS Figure 6: Animating virtual paper characters

  16. SLICING THROUGH TIME IN VIDEOS Figure 7: Slicing through time in a video by deformation

  17. EVALUATION • Two evaluations are done • Tracking performance • User performance of deformation

  18. TRACKING PERFORMANCE Figure 9: Classification of skin. Top: depth input. Center: infrared input. Bottom: depth image after classification with skin parts removed.

  19. USER PERFORMANCE OF DEFORMATION

  20. RESULTS • Figure 11: Average trial completion time in seconds. Error bars show the standard deviation.

  21. CONCLUSIONS • Summary of study findings • Highly flexible displays • Single and dual deformations obtained with high precision level of +/-6 degrees • High accuracy • Average error was below 7mm

  22. CONT… • Touch input on deformable displays • Desired touch area is at the center • Active flexible displays • Available displays are limited • Smart materials • Need for deformable and stretchable

  23. THANK YOU

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