SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Motion editing with spacetime constraints
Proceedings of the 1997 symposium on Interactive 3D graphics
Do geometric models affect judgments of human motion?
Proceedings of the conference on Graphics interface '97
NeuroAnimator: fast neural network emulation and control of physics-based models
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
Physically based motion transformation
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
A hierarchical approach to interactive motion editing for human-like figures
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Automatic Detection of Human Nudes
International Journal of Computer Vision - 1998 Marr Prize
Animation from observation: Motion capture and motion editing
ACM SIGGRAPH Computer Graphics
Composable controllers for physics-based character animation
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Comparing constraint-based motion editing methods
Graphical Models
Motion capture-driven simulations that hit and react
Proceedings of the 2002 ACM SIGGRAPH/Eurographics symposium on Computer animation
Footskate cleanup for motion capture editing
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
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
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
Perception of Human Motion With Different Geometric Models
IEEE Transactions on Visualization and Computer Graphics
Snap-together motion: assembling run-time animations
I3D '03 Proceedings of the 2003 symposium on Interactive 3D graphics
Spacetime Sweeping: An Interactive Dynamic Constraints Solver
CA '02 Proceedings of the Computer Animation
Flexible automatic motion blending with registration curves
Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation
Automated derivation of behavior vocabularies for autonomous humanoid motion
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Efficient synthesis of physically valid human motion
ACM SIGGRAPH 2003 Papers
Geostatistical motion interpolation
ACM SIGGRAPH 2005 Papers
A data-driven approach to quantifying natural human motion
ACM SIGGRAPH 2005 Papers
Knowing when to put your foot down
I3D '06 Proceedings of the 2006 symposium on Interactive 3D graphics and games
A similarity measure for motion stream segmentation and recognition
MDM '05 Proceedings of the 6th international workshop on Multimedia data mining: mining integrated media and complex data
Compression of motion capture databases
ACM SIGGRAPH 2006 Papers
Computational studies of human motion: part 1, tracking and motion synthesis
Foundations and Trends® in Computer Graphics and Vision
Automatic splicing for hand and body animations
Proceedings of the 2006 ACM SIGGRAPH/Eurographics symposium on Computer animation
Quick transitions with cached multi-way blends
Proceedings of the 2007 symposium on Interactive 3D graphics and games
Segmentation and recognition of motion streams by similarity search
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Imposing constraints on fragmented body motion for synthesis
ACM SIGGRAPH 2007 posters
Perceptually consistent example-based human motion retrieval
Proceedings of the 2009 symposium on Interactive 3D graphics and games
Talking bodies: Sensitivity to desynchronization of conversations
ACM Transactions on Applied Perception (TAP)
Toward human-like walking pattern generator
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Space-time curve analogies for motion editing
GMP'08 Proceedings of the 5th international conference on Advances in geometric modeling and processing
Modeling style and variation in human motion
Proceedings of the 2010 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
The parameters effect on performance in ANN for hand gesture recognition system
Expert Systems with Applications: An International Journal
A quantitative methodology to evaluate motion-based animation techniques
MIG'11 Proceedings of the 4th international conference on Motion in Games
Component-based locomotion composition
EUROSCA'12 Proceedings of the 11th ACM SIGGRAPH / Eurographics conference on Computer Animation
Component-based locomotion composition
Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation
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This paper describes a method that can significantly increase the size of a collection of motion observations by cutting limbs from one motion sequence and attaching them to another. Not all such transplants are successful, because correlations across the body are a significant feature of human motion. The method uses randomized search based around a set of rules to generate transplants that are (a) likely to be successful and (b) likely to enrich the existing motion collection. The resulting frames are annotated by a classifier to tell whether they look like human motion or not. We evaluate the method by obtaining motion demands from an application, synthesizing motions to meet those demands, and then scoring the synthesized motions. Motions synthesized using transplants are generally somewhat better than those synthesized without using transplants, because transplanting generates many frames quite close to the original frames, so that it is easier for the motion synthesis process to find a good path in the motion graph. Furthermore, we show classifier errors tend to have relatively little impact in practice. Finally, we show that transplanted motion data can be used to synthesize motions of a group coordinated in space and time without producing motions that share frames.