Machine Learning and Movement Analysis
| Participants: |
Vanessa Yaremchuk Marcelo M. Wanderley (supervisor)
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| Funding: |
NSERC Auditory Cognitive Neuroscience Graduate Fellowship (Yaremchuk)
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| Project Type: |
Doctoral thesis.
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| Time Period: |
Sept. 2010 – present. Status: ongoing.
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Project Description
This project explores the use of different Artificial Neural Network architectures in analysis of motion capture data, towards understanding performer gesture.
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Project Categories
Tags
augmented_instruments
books
brams
breakflute
computer-aided_composition
computer_vision
concert
conducting
conference
digital_orchestra
embedded_development
facequencer
fm_gloves
fmri
force_feedback
guitar
gyrotyre
haptics
hmm
hyper-kalimba
implicit_mapping
imu
interface_design
inverse_kinematics
libmapper
machine_learning
mapping
meta-instrument
motion_capture
movement_analysis
movement_synthesis
music_representation
news
optical_sensing
percussion
performance
pliable_interfaces
sensor_evaluation
sensor_networks
sensors
sonification
sound_spatialization
sound_synthesis
soundcatcher
t-box
t-stick
thumbtec
ultrasound
video_tracking
workshop