1. Implementation of Gesture Recognition in the Immersive Visualization Environment By Danny Catacora Under the guidance of: Judith Terrill and Terence Griffin National Institute of Standards and Technology

2. To add a set of gestures that were intuitive to the users, and have actions that could be easily reconfigured to be applied to different visualizations Problem Statement: Courtesy of capital-benefits-group.com.au

3. Outline: Introduction to the IVE in the RAVE Importance of needed gestures in the IVE Procedure consisted of designing a gesture, record data, and coding it Created similar Wii gestures that are easily defined and recognized Future work includes more complicated gestures

4. Introduction: IVE? Immersive Visualization Environment Produces visualizations from large amounts of computed data A visualization technology that allows human interaction Courtesy of NIST

5. Introduction: Courtesy of NIST RAVE? Reconfigurable Automatic Virtual Environment Takes up the size of a room Consists of a wand, headset, and 3 screens

6. Importance of Problem: Flexible and intuitive navigation methods, but lacks pointer gestures Newer interactions needed Applicable and basic gestures should be investigated Courtesy of NIST

7. Research & Design: Game Technology: The Wii : o Uses a remote controller to recognize gestures Xbox Kinect : o Removes the controller, recognizes human movement and actions Improving 3D Gesture Recognition with Spatially Convenient Input Devices

8. Procedure: Steps for each gesture: Gesture definition: o Specify what happens when the gesture is performed o Define what the gesture program will recognize/look for Data collection: o Figure out how each variable will respond to the gesture o Determine correlations between gestures and changes in position, speed, and acceleration

9. Procedure: Steps for each gesture: Program implementation of gesture: o Write code that will recognize gesture accurately o Use algorithms and data analysis to write code in C++ Gesture testing: o Test the written code for the gesture in both environments o See if calibration for the gesture works

10. Data Interpretation: Had program record the movement of the wand Wand data could be analyzed for specific changes in the x, y, z, yaw, pitch, and roll values. Code was written to catch the patterns of gestures.

11. Results: Resulting algorithms and code that recognizes gestures Further complex gestures later defined from these basic gestures

12. Results: Displaying gesture recognition in the RAVE Display: from terminal, to pop-ups, to 3d arrow

13. Conclusion In the end, able to successfully identify a total 15 gestures Actions completely user definable Gestures will help current interaction within the IVE Set basis for more complex gestures in the future

14. Future Research: Eventually remove the wires, glasses, or the remote Set basis for more complex gestures in the future Establish a greater user-friendly interaction between man and machine in the RAVE

15. Acknowledgments: Judith Terrill- N.I.S.T Terence Griffen- N.I.S.T John Hagedorn- N.I.S.T Steven Satterfield- N.I.S.T Elizabeth Duval - Montgomery Blair High School

16. Thank You. Questions?