External memory algorithms and data structures
External memory algorithms
On-line locomotion generation based on motion blending
Proceedings of the 2002 ACM SIGGRAPH/Eurographics symposium on Computer animation
Understanding Motion Capture for Computer Animation and Video Games
Understanding Motion Capture for Computer Animation and Video Games
Synthesis of complex dynamic character motion from simple animations
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Interactive motion generation from examples
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Interactive control of avatars animated with human motion data
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
An Efficient k-Means Clustering Algorithm: Analysis and Implementation
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Efficient synthesis of physically valid human motion
ACM SIGGRAPH 2003 Papers
Precomputing avatar behavior from human motion data
SCA '04 Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation
Constrained Diameter Steiner Trees for Multicast Conferences in Overlay Networks
QSHINE '04 Proceedings of the First International Conference on Quality of Service in Heterogeneous Wired/Wireless Networks
On-line motion blending for real-time locomotion generation: Research Articles
Computer Animation and Virtual Worlds - Special Issue: The Very Best Papers from CASA 2004
Motion modeling for on-line locomotion synthesis
Proceedings of the 2005 ACM SIGGRAPH/Eurographics symposium on Computer animation
Behavior planning for character animation
Proceedings of the 2005 ACM SIGGRAPH/Eurographics symposium on Computer animation
Proceedings of the 2007 symposium on Interactive 3D graphics and games
Quick transitions with cached multi-way blends
Proceedings of the 2007 symposium on Interactive 3D graphics and games
Active learning for real-time motion controllers
ACM SIGGRAPH 2007 papers
Responsive characters from motion fragments
ACM SIGGRAPH 2007 papers
Near-optimal character animation with continuous control
ACM SIGGRAPH 2007 papers
Construction and optimal search of interpolated motion graphs
ACM SIGGRAPH 2007 papers
Evaluating motion graphs for character animation
ACM Transactions on Graphics (TOG)
Evaluating Steiner-tree heuristics and diameter variations for application layer multicast
Computer Networks: The International Journal of Computer and Telecommunications Networking
Proceedings of the 2008 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Achieving good connectivity in motion graphs
Proceedings of the 2008 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
ACM SIGGRAPH Asia 2009 papers
Synchronized partial-body motion graphs
ACM SIGGRAPH ASIA 2010 Sketches
A framework for motion based bodily enaction with virtual characters
IVA'11 Proceedings of the 10th international conference on Intelligent virtual agents
Feature-Based locomotion with inverse branch kinematics
MIG'11 Proceedings of the 4th international conference on Motion in Games
Automating expressive locomotion generation
Transactions on Edutainment VII
Interactive buildup of animation sequences with captured motion data
Computer Animation and Virtual Worlds
Hybrid motion graph for character motion synthesis
Journal of Visual Languages and Computing
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Motion capture data have been used effectively in many areas of human motion synthesis. Among those, motion graph-based approaches have shown great promise for novice users due to their ability to generate long motions and the fully automatic process of motion synthesis. The performance of motion graph based approaches, however, relies heavily on selecting a good set of motions used to build the graph. This motion set needs to contain enough motions to achieve good connectivity and smooth transitions. At the same time, the motion set needs to be small for fast motion synthesis. Manually selecting a good motion set that achieves these requirements is difficult, especially given that motion capture databases are growing larger to provide a richer variety of human motions. Therefore we propose an automatic approach to select a good motion set. We cast the motion selection problem as a search for a minimum size subgraph from a large motion graph representing the motion capture database and propose an efficient algorithm, called the Iterative Sub-graph Algorithm, to find a good approximation to the optimal solution. Our approach especially benefits novice users who desire simple and fully automatic motion synthesis tools, such as motion graph-based techniques.