Fundamentals of speech recognition
Fundamentals of speech recognition
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Morphable Models for the Analysis and Synthesis of Complex Motion Patterns
International Journal of Computer Vision - special issue on learning and vision at the center for biological and computational learning, Massachusetts Institute of Technology
Motion capture assisted animation: texturing and synthesis
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Automated Derivation of Primitives for Movement Classification
Autonomous Robots
Verbs and Adverbs: Multidimensional Motion Interpolation
IEEE Computer Graphics and Applications
Flexible automatic motion blending with registration curves
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Motion synthesis from annotations
ACM SIGGRAPH 2003 Papers
Segmenting motion capture data into distinct behaviors
GI '04 Proceedings of the 2004 Graphics Interface Conference
Automated extraction and parameterization of motions in large data sets
ACM SIGGRAPH 2004 Papers
Motion map: image-based retrieval and segmentation of motion data
SCA '04 Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation
A system for analyzing and indexing human-motion databases
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Action synopsis: pose selection and illustration
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Efficient content-based retrieval of motion capture data
ACM SIGGRAPH 2005 Papers
Performance animation from low-dimensional control signals
ACM SIGGRAPH 2005 Papers
Dynamic response for motion capture animation
ACM SIGGRAPH 2005 Papers
Style translation for human motion
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An efficient search algorithm for motion data using weighted PCA
Proceedings of the 2005 ACM SIGGRAPH/Eurographics symposium on Computer animation
Indexing large human-motion databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
IEEE Transactions on Circuits and Systems for Video Technology
Database techniques with motion capture
ACM SIGGRAPH 2007 courses
An Evolutionary Approach for Learning Motion Class Patterns
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An efficient algorithm for keyframe-based motion retrieval in the presence of temporal deformations
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Perceptually consistent example-based human motion retrieval
Proceedings of the 2009 symposium on Interactive 3D graphics and games
Motion Belts: Visualization of Human Motion Data on a Timeline
IEICE - Transactions on Information and Systems
Learning Actions through Imitation and Exploration: Towards Humanoid Robots That Learn from Humans
Creating Brain-Like Intelligence
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 and retrieval of human motion data by a hierarchical tree
Proceedings of the 16th ACM Symposium on Virtual Reality Software and Technology
Automated analysis of performance variations in folk song recordings
Proceedings of the international conference on Multimedia information retrieval
Fast local and global similarity searches in large motion capture databases
Proceedings of the 2010 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Real-time classification of dance gestures from skeleton animation
SCA '11 Proceedings of the 2011 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
A puppet interface for retrieval of motion capture data
SCA '11 Proceedings of the 2011 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Towards cross-modal comparison of human motion data
DAGM'11 Proceedings of the 33rd international conference on Pattern recognition
Pattern Recognition Letters
Recognition of gesture sequences in real-time flow, context of virtual theater
GW'09 Proceedings of the 8th international conference on Gesture in Embodied Communication and Human-Computer Interaction
Generalized Model-Based Human Motion Recognition with Body Partition Index Maps
Computer Graphics Forum
Interaction Retrieval by Spacetime Proximity Graphs
Computer Graphics Forum
Motion retrieval based on kinetic features in large motion database
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Human motion retrieval using topic model
Computer Animation and Virtual Worlds
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
Exploring the Trade-off Between Accuracy and Observational Latency in Action Recognition
International Journal of Computer Vision
Efficient motion retrieval in large motion databases
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3D motion retrieval based on double index and user interaction
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Human-virtual human interaction by upper body gesture understanding
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Online RGB-D gesture recognition with extreme learning machines
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Ongoing human action recognition with motion capture
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Online gesture recognition from pose kernel learning and decision forests
Pattern Recognition Letters
Hybrid motion graph for character motion synthesis
Journal of Visual Languages and Computing
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This paper presents new methods for automatic classification and retrieval of motion capture data facilitating the identification of logically related motions scattered in some database. As the main ingredient, we introduce the concept of motion templates (MTs), by which the essence of an entire class of logically related motions can be captured in an explicit and semantically interpretable matrix representation. The key property of MTs is that the variable aspects of a motion class can be automatically masked out in the comparison with unknown motion data. This facilitates robust and efficient motion retrieval even in the presence of large spatio-temporal variations. Furthermore, we describe how to learn an MT for a specific motion class from a given set of training motions. In our extensive experiments, which are based on several hours of motion data, MTs proved to be a powerful concept for motion annotation and retrieval, yielding accurate results even for highly variable motion classes such as cartwheels, lying down, or throwing motions.