virtual sports for real! · virtual sports in the future •run with virtual trainer •run with...
TRANSCRIPT
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Virtual Sports for Real!
Elmar Eisemann1 and Stephan Lukosch2
1Computer Graphics and Visualization, Faculty of Electrical Engineering, Mathematics and Computer Science 2Systems Engineering Section, Faculty of Technology, Policy and Management
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Outline
• Virtual Sports
• Creating virtual worlds for sports
• Virtual reality equipment
• Motion data analysis and visualization
• Outlook
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VIRTUAL SPORTS
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Virtual Sports https://www.youtube.com/watch?v=FdyeWExPZYg
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Virtual Sports in the Future
• Physically train and exercise
• Create controlled environments
• Perform precise measurements
• Provide personalized and adaptive real-time coaching
• Foster engagement and motivation for sports
http://cdn.theatlantic.com/assets/media/img/sponsored/2014/09/article_4/resp-feature.jpg?1427821271
http://cdn.theatlantic.com/assets/media/img/sponsored/2014/09/article_2/resp-feature.jpg?1427821241
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Virtual Sports in the Future
• Run with virtual trainer
• Run with other runners on the same track sharing performance details
• Run against ghosts, i.e. runners that have run here before
• Run with runners somewhere else on the world
• Run on a treadmill for precise gait evaluation and training
http://numrush.com/2013/11/07/glassfit-puts-fun-excitement-back-running-using-augmented-reality/
http://www.teach42.com/2014/01/15/20-things-you-cant-do-with-glass-but-you-really-can/
https://www.youtube.com/watch?v=NKhh3Q2zYDA
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Superhuman sports
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CREATING VIRTUAL WORLDS FOR TRAINING
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Overview
• Several Different Creation Scenarios
• Real-world Environments
• Reproduction of Particular Scenarios
• Free-Form Design of Virtual Environments
automatic
user interaction
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Creating Virtual Worlds with Real-world Data
• AHN 2 Data Set – 8 TB [Kehl, Tutenel, de Hahn, Eisemann – Geos. World F.2013]
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Geometry Recognition
here 128 M points in 2 min
[Sunkel, Jansen, Wand, Eisemann, Seidel - EG 2012][Silva, Eisemann, Bidarra, Coelho - PCG 2015]
[Wu, Wand, Hildebrandt, Jansen, Seidel - 3DV 2014]
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Tools for Creating Virtual Environments[Smelik, Tutenel, Kraker, Bidarra – C&G 2010]
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Making Environments Look Realistic[Klehm, Seidel, Eisemann – TVCG 2016]
[Holländer, Ritschel, Eisemann, Boubekeur - EGSR 2011][Ritschel, Eisemann, Ha, Kim, Seidel - CGF 2011]
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VIRTUAL REALITY EQUIPMENT
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Virtual Reality Display Options
Samsung Gear VR Oculus Rift
HTC Vive
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A Large Field-of-View Solution for Eye-tracking HMDs
• Main difficulties: • Maintain Large Field of View• Solve Calibration due to Fabrication Imperfections
[Stengel, Grogorick, Eisemannx2, Magnor – ACM MM 2015]
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A Large Field-of-View Solution for Eye-tracking HMDs
• Gaze evaluation useful for…• Gaze Evaluation• Gaze-contingent Rendering• Interaction with Avatars• ...
[Stengel, Grogorick, Eisemannx2, Magnor – ACM MM 2015]
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Augmented Reality
• Fusion of Virtual and Real World
[Baboud, Cadik, Eisemann, Seidel – CVPR’11]
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DATA ANALYSIS AND VISUALIZATION
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Motivation
• Need for assessment methods that allow for • objective, quantitative and valid measures • identifying the factors contributing to motor dysfunction
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Motion Tracking
Microsoft Kinect
Intel RealSense
Perception Neuron
HTC Vive controller
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AR technology Serious game
Assessment tool
Approach Cidota, Lukosch, Bank (2015)
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Study on game engagement and usability
• Study with 8 healthy people older than 50 years
• Epson Moverio BT-200 OST-HMD with an Intel® RealSense F200 RGB-D camera
• Participants sorted a set of ten packages each
• Session recorded and debriefed
• Game Experience Questionnaire (GEQ)
• System Usability Survey (SUS)
Dezentje et al. (2015)
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Results
• Liked the game
• Needs practice
• Difficult depth perception
• Difficult head-hand coordination
• Data from the sensors • positions and orientations of the joints
approx. 15MB per minute• RGB and RGB-D video stream
each approx. 4MB per minute • per patient and session more than 1GB
• Offline data analysis necessary for validation
Cidota et al. (2015)
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Inertial Measurement Unit
• Record movement of the person
www.motionnode.com
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Analyze such Data?
• Sensor output in a scatterplot• Often not very readable
• Dimensionality Reduction
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Dimensionality Reduction - Example
Costly offline process
[Van der Maaten and Hinton 2008]
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Interactive t-SNE Clustering[Pezzotti, Höllt, Lelieveldt, Eisemann, Vilanova - EuroVis2016]
TU Delft Sports Engineering Institute
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Various Sensors and Data Sources
• Health Apps:
• FitBit
• Garmin
• SHealth
• iOS 9 – Health
• MapMyFitness
• …
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Analysis and Visualization Tools for Complex or High-Dimensional Data
[Raidou, Eisemann , Breeuwer, Eisemann, Vilanova - Vis2015]
[de Hoon, van Pelt, Jalba, Vilanova – CGF15] [Kroes, Eisemannx2 – GI15]
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OUTLOOK
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Outlook
• New Sports Challenges
• Adaptive Environments
• New Sensors and On-the-fly Data Analysis
• Advanced Virtual Reality Equipment
• Engagement and Gamification
• Data Analysis and Visualization Solutions
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Thank you very muchfor your attention!
Elmar EisemannComputer Graphics & Visualizationhttp://graphics.tudelft.nl/[email protected]
Stephan LukoschSystems Engineeringhttp://www.tudelft.nl/[email protected]