Efficient Physics-Based Implementation for Realistic Hand-Object Interaction in Virtual Reality

We propose an efficient physics-based method for dexterous ‘real hand’ - ‘virtual object’ interaction in Virtual Reality environments. Our method is based on the Coulomb friction model, and we show how to efficiently implement it in a commodity VR engine for realtime performance. This model enables very convincing simulations of many types of actions such as pushing, pulling, grasping, or even dexterous manipulations such as spinning objects between fingers without restrictions on the objects' shapes or hand poses. Because it is an analytic model, we do not require any prerecorded data, in contrast to previous methods. For the evaluation of our method, we conduction a pilot study that shows that our method is perceived more realistic and natural, and allows for more diverse interactions. Further, we evaluate the computational complexity of our method to show real-time performance in VR environments.

[1]  M. Gafvert Comparisons of two dynamic friction models , 1997, Proceedings of the 1997 IEEE International Conference on Control Applications.

[2]  Bernd Fröhlich,et al.  A soft hand model for physically-based manipulation of virtual objects , 2011, 2011 IEEE Virtual Reality Conference.

[3]  Michael Ortega-Binderberger,et al.  A Six Degree-of-Freedom God-Object Method for Haptic Display of Rigid Bodies with Surface Properties , 2007, IEEE Transactions on Visualization and Computer Graphics.

[4]  Bernd Fröhlich,et al.  A generalized God-object method for plausible finger-based interactions in virtual environments , 2012, 2012 IEEE Symposium on 3D User Interfaces (3DUI).

[5]  Chris Hand,et al.  A Survey of 3D Interaction Techniques , 1997, Comput. Graph. Forum.

[6]  Steven D. Pieper,et al.  Hands-on interaction with virtual environments , 1989, UIST '89.

[7]  Yuval Tassa,et al.  MuJoCo: A physics engine for model-based control , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[8]  Maud Marchal,et al.  Aggregate Constraints for Virtual Manipulation with Soft Fingers , 2015, IEEE Transactions on Visualization and Computer Graphics.

[9]  David Kim,et al.  HoloDesk: direct 3d interactions with a situated see-through display , 2012, CHI.

[10]  Thomas Brox,et al.  Learning to Estimate 3D Hand Pose from Single RGB Images , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[11]  Zhengyou Zhang,et al.  Microsoft Kinect Sensor and Its Effect , 2012, IEEE Multim..

[12]  Christoph W. Borst,et al.  Realistic virtual grasping , 2005, IEEE Proceedings. VR 2005. Virtual Reality, 2005..

[13]  A. Mak,et al.  In vivo friction properties of human skin , 1999, Prosthetics and orthotics international.

[14]  Dieter Schmalstieg,et al.  Integration of the HTC Vive into the medical platform MeVisLab , 2017, Medical Imaging.

[15]  Christoph W. Borst,et al.  Virtual grasp release method and evaluation , 2012, Int. J. Hum. Comput. Stud..

[16]  Emiko Charbonneau,et al.  The Wiimote and Beyond: Spatially Convenient Devices for 3D User Interfaces , 2010, IEEE Computer Graphics and Applications.

[17]  Carlos Canudas de Wit,et al.  Friction Models and Friction Compensation , 1998, Eur. J. Control.

[18]  D. P. Young,et al.  A locally refined rectangular grid finite element method: application to computational fluid dynamics and computational physics , 1990 .

[19]  Young J. Kim,et al.  Physics-based Interactive Virtual Grasping , 2016 .

[20]  Andy Cockburn,et al.  FingARtips: gesture based direct manipulation in Augmented Reality , 2004, GRAPHITE '04.

[21]  Miguel A. Otaduy,et al.  Interactive simulation of a deformable hand for haptic rendering , 2011, 2011 IEEE World Haptics Conference.

[22]  Andrew W. Fitzgibbon,et al.  Efficient and precise interactive hand tracking through joint, continuous optimization of pose and correspondences , 2016, ACM Trans. Graph..

[23]  Pavlo Molchanov,et al.  Online Detection and Classification of Dynamic Hand Gestures with Recurrent 3D Convolutional Neural Networks , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[24]  Jun-Sik Kim,et al.  Direct and realistic handover of a virtual object , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[25]  Peter J. Gawthrop,et al.  A nonlinear disturbance observer for robotic manipulators , 2000, IEEE Trans. Ind. Electron..

[26]  Frank Maurer,et al.  Gesture-driven Interactions on a Virtual Hologram in Mixed Reality , 2016, ISS Companion.

[27]  Diego Gutierrez,et al.  To stylize or not to stylize? , 2015, ACM Trans. Graph..

[28]  Henrik I. Christensen,et al.  Automatic grasp planning using shape primitives , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[29]  Mike Bailey,et al.  Augment Your Reality , 2016, IEEE Computer Graphics and Applications.

[30]  Alexei Sourin,et al.  Function-based approach to mixed haptic effects rendering , 2011, The Visual Computer.

[31]  Vladimir Pavlovic,et al.  Visual Interpretation of Hand Gestures for Human-Computer Interaction: A Review , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[32]  Joze Guna,et al.  An Analysis of the Precision and Reliability of the Leap Motion Sensor and Its Suitability for Static and Dynamic Tracking , 2014, Sensors.

[33]  Ying Li,et al.  Data-Driven Grasp Synthesis Using Shape Matching and Task-Based Pruning , 2007, IEEE Transactions on Visualization and Computer Graphics.

[34]  Daniel Thalmann,et al.  Simulation of object and human skin formations in a grasping task , 1989, SIGGRAPH.

[35]  Anthony Bracegirdle Investigating the Usability of the Leap Motion Controller: Gesture-Based Interaction with a 3D Virtual Environment , 2014 .

[36]  Bernd Fröhlich,et al.  Effective manipulation of virtual objects within arm's reach , 2011, 2011 IEEE Virtual Reality Conference.

[37]  Miguel A. Otaduy,et al.  Strain limiting for soft finger contact simulation , 2013, 2013 World Haptics Conference (WHC).

[38]  Jun-Sik Kim,et al.  Physics-based hand interaction with virtual objects , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[39]  Jinxiang Chai,et al.  Robust realtime physics-based motion control for human grasping , 2013, ACM Trans. Graph..

[40]  Anupam Agrawal,et al.  Vision based hand gesture recognition for human computer interaction: a survey , 2012, Artificial Intelligence Review.

[41]  Rafael Kelly,et al.  A measurement procedure for viscous and coulomb friction , 2000, IEEE Trans. Instrum. Meas..

[42]  Tae-Yong Kim,et al.  Unified particle physics for real-time applications , 2014, ACM Trans. Graph..

[43]  Yuval Tassa,et al.  Simulation tools for model-based robotics: Comparison of Bullet, Havok, MuJoCo, ODE and PhysX , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[44]  François Bérard,et al.  Bare-hand human-computer interaction , 2001, PUI '01.

[45]  Vincent Lepetit,et al.  Hands Deep in Deep Learning for Hand Pose Estimation , 2015, ArXiv.

[46]  Michael Girard,et al.  Computer animation of knowledge-based human grasping , 1991, SIGGRAPH.

[47]  Cagatay Basdogan,et al.  A Ray-Based Haptic Rendering Technique for Displaying Shape and Texture of 3D Objects in Virtual Environments , 1997, Dynamic Systems and Control.

[48]  Christoph W. Borst,et al.  Visual feedback for virtual grasping , 2014, 2014 IEEE Symposium on 3D User Interfaces (3DUI).

[49]  Andrew Wilson,et al.  MirageTable: freehand interaction on a projected augmented reality tabletop , 2012, CHI.

[50]  Christoph W. Borst,et al.  A Spring Model for Whole-Hand Virtual Grasping , 2006, Presence: Teleoperators & Virtual Environments.

[51]  Victor B. Zordan,et al.  Physically based grasping control from example , 2005, SCA '05.