SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
The visual analysis of human movement: a survey
Computer Vision and Image Understanding
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
A survey of computer vision-based human motion capture
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Learning variable-length Markov models of behavior
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Comparing constraint-based motion editing methods
Graphical Models
Footskate cleanup for motion capture editing
Proceedings of the 2002 ACM SIGGRAPH/Eurographics symposium on Computer animation
Interactive control of avatars animated with human motion data
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
On Learning the Shape of Complex Actions
IWVF-4 Proceedings of the 4th International Workshop on Visual Form
BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
Learning and Recognizing Human Dynamics in Video Sequences
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
MVIEW '99 Proceedings of the IEEE Workshop on Multi-View Modeling & Analysis of Visual Scenes
BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
Style translation for human motion
ACM SIGGRAPH 2005 Papers
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In this paper we present an approach for the modeling complex movement sequences. Based on the method of Spatio-Temporal Morphable Models (STMMs) [11] we derive a new hierarchical algorithm that, in a first step, identifies movement elements in the complex movement sequence based on characteristic events, and in a second step quantifies these movement primitives by approximation through linear combinations of learned example movement trajectories. The proposed algorithm is used to segment and to morph sequences of karate movements of different people and different styles.