3-D character animation using motion capture
Interactive computer animation
Computer puppetry: An importance-based approach
ACM Transactions on Graphics (TOG)
Motion capture assisted animation: texturing and synthesis
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Flexible automatic motion blending with registration curves
Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation
Motion synthesis from annotations
ACM SIGGRAPH 2003 Papers
Layered acting for character animation
ACM SIGGRAPH 2003 Papers
Efficient content-based retrieval of motion capture data
ACM SIGGRAPH 2005 Papers
Performance animation from low-dimensional control signals
ACM SIGGRAPH 2005 Papers
Motion synthesis and editing in low-dimensional spaces: Research Articles
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Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Active learning for real-time motion controllers
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Practical motion capture in everyday surroundings
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Simulating biped behaviors from human motion data
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Indexing large human-motion databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions
Communications of the ACM - 50th anniversary issue: 1958 - 2008
Real-time data driven deformation using kernel canonical correlation analysis
ACM SIGGRAPH 2008 papers
Accelerometer-based user interfaces for the control of a physically simulated character
ACM SIGGRAPH Asia 2008 papers
Action capture with accelerometers
Proceedings of the 2008 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Motion fields for interactive character locomotion
ACM SIGGRAPH Asia 2010 papers
Fast local and global similarity searches in large motion capture databases
Proceedings of the 2010 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Motion capture from body-mounted cameras
ACM SIGGRAPH 2011 papers
Towards cross-modal comparison of human motion data
DAGM'11 Proceedings of the 33rd international conference on Pattern recognition
Quantifying human reconstruction accuracy for voxelcarving in a sporting environment
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Accurate realtime full-body motion capture using a single depth camera
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
Real-time physical modelling of character movements with microsoft kinect
Proceedings of the 18th ACM symposium on Virtual reality software and technology
Efficient motion retrieval in large motion databases
Proceedings of the ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games
Model based full body human motion reconstruction from video data
Proceedings of the 6th International Conference on Computer Vision / Computer Graphics Collaboration Techniques and Applications
Reconstructing whole-body motions with wrist trajectories
Graphical Models
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The development of methods and tools for the generation of visually appealing motion sequences using prerecorded motion capture data has become an important research area in computer animation. In particular, data-driven approaches have been used for reconstructing high-dimensional motion sequences from low-dimensional control signals. In this article, we contribute to this strand of research by introducing a novel framework for generating full-body animations controlled by only four 3D accelerometers that are attached to the extremities of a human actor. Our approach relies on a knowledge base that consists of a large number of motion clips obtained from marker-based motion capturing. Based on the sparse accelerometer input a cross-domain retrieval procedure is applied to build up a lazy neighborhood graph in an online fashion. This graph structure points to suitable motion fragments in the knowledge base, which are then used in the reconstruction step. Supported by a kd-tree index structure, our procedure scales to even large datasets consisting of millions of frames. Our combined approach allows for reconstructing visually plausible continuous motion streams, even in the presence of moderate tempo variations which may not be directly reflected by the given knowledge base.