Retargetting motion to new characters
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
The EMOTE model for effort and shape
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
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
Motion synthesis from annotations
ACM SIGGRAPH 2003 Papers
Segmenting motion capture data into distinct behaviors
GI '04 Proceedings of the 2004 Graphics Interface Conference
Motion doodles: an interface for sketching character motion
ACM SIGGRAPH 2004 Papers
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
Acquiring and validating motion qualities from live limb gestures
Graphical Models
A system for analyzing and indexing human-motion databases
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Action synopsis: pose selection and illustration
ACM SIGGRAPH 2005 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 retrieval based on movement notation language: Motion Capture and Retrieval
Computer Animation and Virtual Worlds - CASA 2005
Motion templates for automatic classification and retrieval of motion capture data
Proceedings of the 2006 ACM SIGGRAPH/Eurographics symposium on Computer animation
MotionMaster: authoring and choreographing Kung-fu motions by sketch drawings
Proceedings of the 2006 ACM SIGGRAPH/Eurographics symposium on Computer animation
Motion cues for illustration of skeletal motion capture data
Proceedings of the 5th international symposium on Non-photorealistic animation and rendering
Indexing large human-motion databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Statistical analysis of natural human motion for animation
Statistical analysis of natural human motion for animation
Semantic Segmentation of Motion Capture Using Laban Movement Analysis
IVA '07 Proceedings of the 7th international conference on Intelligent Virtual Agents
Perceptually consistent example-based human motion retrieval
Proceedings of the 2009 symposium on Interactive 3D graphics and games
Indexing and retrieval of human motion data by a hierarchical tree
Proceedings of the 16th ACM Symposium on Virtual Reality Software and Technology
IEC-based motion retrieval system using Laban movement analysis
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part IV
Motion reconstruction using sparse accelerometer data
ACM Transactions on Graphics (TOG)
A puppet interface for retrieval of motion capture data
SCA '11 Proceedings of the 2011 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
An efficient keyframe extraction from motion capture data
CGI'06 Proceedings of the 24th international conference on Advances in Computer Graphics
Retrieval and Visualization of Human Motion Data via Stick Figures
Computer Graphics Forum
Motion indexing of different emotional states using LMA components
SIGGRAPH Asia 2013 Technical Briefs
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There has been a recent paradigm shift in the computer animation industry with an increasing use of pre-recorded motion for animating virtual characters. A fundamental requirement to using motion capture data is an efficient method for indexing and retrieving motions. In this paper, we propose a flexible, efficient method for searching arbitrarily complex motions in large motion databases. Motions are encoded using keys which represent a wide array of structural, geometric and, dynamic features of human motion. Keys provide a representative search space for indexing motions and users can specify sequences of key values as well as multiple combination of key sequences to search for complex motions. We use a trie-based data structure to provide an efficient mapping from key sequences to motions. The search times (even on a single CPU) are very fast, opening the possibility of using large motion data sets in real-time applications.