Locally Weighted Learning for Control
Artificial Intelligence Review - Special issue on lazy learning
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Motion texture: a two-level statistical model for character motion synthesis
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Clustered Partial Linear Regression
Machine Learning
Locally Weighted Projection Regression: Incremental Real Time Learning in High Dimensional Space
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
A New Learning Method for Piecewise Linear Regression
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Learning and Synthesizing Human Body Motion and Posture
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Mapping Algorithms for Real-Time Control of an Avatar Using Eight Sensors
Presence: Teleoperators and Virtual Environments
Indexing large human-motion databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Search and transitioning for motion captured sequences
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Motion templates for automatic classification and retrieval of motion capture data
Proceedings of the 2006 ACM SIGGRAPH/Eurographics symposium on Computer animation
Database techniques with motion capture
ACM SIGGRAPH 2007 courses
Compression of human motion animation using the reduction of interjoint correlation
Journal on Image and Video Processing - Anthropocentric Video Analysis: Tools and Applications
HCI Beyond the GUI: Design for Haptic, Speech, Olfactory, and Other Nontraditional Interfaces
HCI Beyond the GUI: Design for Haptic, Speech, Olfactory, and Other Nontraditional Interfaces
Perceptually consistent example-based human motion retrieval
Proceedings of the 2009 symposium on Interactive 3D graphics and games
Efficient and robust annotation of motion capture data
Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Proceedings of the 2008 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Indexing 3-D human motion repositories for content-based retrieval
IEEE Transactions on Information Technology in Biomedicine - Special section on computational intelligence in medical systems
A group of novel approaches and a toolkit for motion capture data reusing
Multimedia Tools and Applications
Semantic quantization of 3D human motion capture data through spatial-temporal feature extraction
MMM'08 Proceedings of the 14th international conference on Advances in multimedia modeling
A generic approach to design and querying of multi-purpose human motion database
ICCVG'10 Proceedings of the 2010 international conference on Computer vision and graphics: Part I
Knowledge discovery from 3D human motion streams through semantic dimensional reduction
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Real-time classification of dance gestures from skeleton animation
SCA '11 Proceedings of the 2011 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Hierarchical indexing structure for 3d human motions
MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
An information retrieval system for motion capture data
ECIR'06 Proceedings of the 28th European conference on Advances in Information Retrieval
Quaternion space sparse decomposition for motion compression and retrieval
EUROSCA'12 Proceedings of the 11th ACM SIGGRAPH / Eurographics conference on Computer Animation
Quaternion space sparse decomposition for motion compression and retrieval
Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Efficient motion retrieval in large motion databases
Proceedings of the ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games
3D motion retrieval based on double index and user interaction
International Journal of Information and Communication Technology
Motion indexing of different emotional states using LMA components
SIGGRAPH Asia 2013 Technical Briefs
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We demonstrate a data-driven approach for representing, compressing, and indexing human-motion databases. Our modeling approach is based on piecewise-linear components that are determined via a divisive clustering method. Selection of the appropriate linear model is determined automatically via a classifier using a subspace of the most significant, or principle features (markers). We show that, after offline training, our model can accurately estimate and classify human motions. We can also construct indexing structures for motion sequences according to their transition trajectories through these linear components. Our method not only provides indices for whole and/or partial motion sequences, but also serves as a compressed representation for the entire motion database. Our method also tends to be immune to temporal variations, and thus avoids the expense of time-warping.