Data-driven animation of hand-object interactions

Animating hand-object interactions is a frequent task in applications such as the production of 3d movies. Unfortunately this task is difficult due to the hand's many degrees of freedom and the constraints on the hand motion imposed by the geometry of the object. However, the causality between the object state and the hand's pose can be exploited in order to simplify the animation process. In this paper, we present a method that takes an animation of an object as input and automatically generates the corresponding hand motion. This approach is based on the simple observation that objects are easier to animate than hands, since they usually have fewer degrees of freedom. The method is data-driven; sequences of hands manipulating an object are captured semi-automatically with a structured-light setup. The training data is then combined with a new animation of the object in order to generate a plausible animation featuring the hand-object interaction.

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

[2]  Marc Levoy,et al.  Real-time 3D model acquisition , 2002, ACM Trans. Graph..

[3]  E. Reed The Ecological Approach to Visual Perception , 1989 .

[4]  Jianwei Zhang,et al.  Learning of demonstrated grasping skills by stereoscopic tracking of human head configuration , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[5]  Karan Singh,et al.  Eurographics/siggraph Symposium on Computer Animation (2003) Handrix: Animating the Human Hand , 2003 .

[6]  Luc Van Gool,et al.  Tracking a hand manipulating an object , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[7]  Danica Kragic,et al.  Grasp Recognition for Programming by Demonstration , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[8]  Luc Van Gool,et al.  Fast 3D Scanning with Automatic Motion Compensation , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[9]  Dinesh K. Pai,et al.  Interaction capture and synthesis , 2005, SIGGRAPH 2005.

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

[11]  Nadia Magnenat-Thalmann,et al.  Neural network-based violinist's hand animation , 2000, Proceedings Computer Graphics International 2000.

[12]  C. Karen Liu Dextrous manipulation from a grasping pose , 2009, SIGGRAPH 2009.

[13]  Danica Kragic,et al.  Hands in action: real-time 3D reconstruction of hands in interaction with objects , 2010, 2010 IEEE International Conference on Robotics and Automation.

[14]  Hans-Peter Seidel,et al.  Eurographics/siggraph Symposium on Computer Animation (2003) Construction and Animation of Anatomically Based Human Hand Models , 2022 .

[15]  Kang-Hyun Jo,et al.  Manipulative hand gesture recognition using task knowledge for human computer interaction , 1998, Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition.

[16]  C. Karen Liu,et al.  Eurographics/ Acm Siggraph Symposium on Computer Animation (2008) Synthesis of Interactive Hand Manipulation , 2022 .

[17]  Danica Kragic,et al.  Simultaneous Visual Recognition of Manipulation Actions and Manipulated Objects , 2008, ECCV.

[18]  Luc Van Gool,et al.  An object-dependent hand pose prior from sparse training data , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[19]  Mubarak Shah,et al.  View-Invariant Representation and Recognition of Actions , 2002, International Journal of Computer Vision.

[20]  Ashutosh Saxena,et al.  Robotic Grasping of Novel Objects using Vision , 2008, Int. J. Robotics Res..

[21]  Mark R. Cutkosky,et al.  Modeling manufacturing grips and correlations with the design of robotic hands , 1986, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

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

[23]  Vijay Kumar,et al.  Robotic grasping and contact: a review , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).