Performance physics Analysis and synthesis of communicative bodies
Item
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Title
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Performance physics Analysis and synthesis of communicative bodies
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Identifier
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d_2009_2013:34919a161ef9:11383
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identifier
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11761
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Creator
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Schultz, Anthony,
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Contributor
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Brian Schwartz
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Date
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2012
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Language
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English
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Publisher
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City University of New York.
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Subject
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Biophysics | Biomechanics | Dance | communication | cybernetics | human kinematics | motion graphs | motion spectra | performance
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Abstract
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Human motion contains information like written or spoken language. Contemporary camera and computer technologies capture this information for gaming, animation, medical diagnostics and robotic control. In this thesis we model human performance recorded with motion capture and video. Beginning with a kinematic chain model of the human body we generate a metric for comparing different states of skeletal articulation. Applying this measure over motion data time series generates similarity spectra from which we identify and characterize body motions. We use the results to model the subject's underlying movement vocabulary with a network of connected recordings called a motion graph. We construct a set of motion graphs from video data and by assigning variable transition probabilities between recorded movement sequences we model the purposeful subject as a stochastic traversal process on the motion graph. Finally we present the application of a non-anatomical kinematic chain model to video data and derive the accompanying distance metrics. We discuss the results and possible applications of these techniques.
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Type
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dissertation
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Source
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2009_2013.csv
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degree
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Ph.D.
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Program
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Physics
