Publication | Closed Access
Automatic Hand-Over Animation using Principle Component Analysis
38
Citations
18
References
2013
Year
Unknown Venue
EngineeringHuman Pose Estimation3D Pose EstimationComputer AnimationComputer-aided DesignSparse MarkerImage AnalysisKinesiologyPrinciple Component AnalysisMotion CaptureSystems EngineeringKinematicsRobot LearningGesture ProcessingHealth SciencesMachine VisionDanceDesignComputer VisionGesture RecognitionEye TrackingExtended RealitySmall NumberHand AnimationHuman Movement
This paper introduces a method for producing high quality hand motion using a small number of markers. The proposed "handover" animation technique constructs joint angle trajectories with the help of a reference database. Utilizing principle component analysis (PCA) applied to the database, the system automatically determines the sparse marker set to record. Further, to produce hand animation, PCA is used along with a locally weighted regression (LWR) model to reconstruct joint angles. The resulting animation is a full-resolution hand which reflects the original motion without the need for capturing a full marker set. Comparing the technique to other methods reveals improvement over the state of the art in terms of the marker set selection. In addition, the results highlight the ability to generalize the motion synthesized, both by extending the use of a single reference database to new motions, and from distinct reference datasets, over a variety of freehand motions.
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