Statistical models of ear shape and ear acoustics
Summary
The future of personal audio devices relies on statistical shape analysis of ears and ear acoustics. We have the world’s largest database of head-ear meshes together with ear acoustic data. The task is to explore statistical models of these data and apply leading machine learning techniques to map the data.
Supervisor(s)
Associate Professor Craig Jin, Professor Philip Leong, Professor Alistair McEwan
Research Location
Electrical and Information Engineering
Program Type
Masters/PHD
Synopsis
This leading research project explores advanced mathematical techniques for statistical shape analysis of ears and ear acoustics. Advanced machine learning techniques will be applied to map shape data to acoustic data. Topics include pattern theory and generative statistical models. We will work with leading international research teams.
Additional Information
Successful candidates likely have a background in mathematical modeling and machine learning.
http://www.ee.usyd.edu.au/carlab
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Keywords
Statistical shape analysis, Machine learning, morphable models, head-related transfer functions, Spatial Audio, ear shape, 3D shape from 2D images, 3D
Opportunity ID
The opportunity ID for this research opportunity is: 1359
Other opportunities with Associate Professor Craig Jin
- Pattern analysis techniques for sound synthesis
- Interpolation of binaural impulse responses for virtual auditory displays
- Sound field recording and recreation
- Beamforming with acoustic vector sensors - Multiple acoustic source localisation using acoustic vector sensor arrays
- Speech separation and localisation using particle filtering
- Mapping 2D Images to 3D Shape
- New technique for studying human brain activity
- Next Generation Audio Coding
- Spherical multi-modal scene analysis
- Binaural signal processing algorithms for hearing aids
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- Impedance tomography for cardiac imaging: high speed tomography
- Medical diagnostics for neonates in the developing world
- FPGA-based Low Latency Trading
- Floating Point FPGA Architectures
- Placement-aware Hardware Description Languages
- Scalable vision machines
- Modelling Parkinson's disease using control models
- Novel Electrodes for rapid electrophysiological recording
- FPGA-based low latency machine learning
Other opportunities with Professor Philip Leong
- other research opportunities available at Faculty of Engineering
- FPGA-based Low Latency Trading
- Floating Point FPGA Architectures
- Placement-aware Hardware Description Languages
- Domain-specific Languages for GPU-based Computing
- Scalable vision machines
- Modelling Parkinson's disease using control models
- FPGA-based low latency machine learning
- FPGA control of photonic systems
- Test
- Mapping 2D Images to 3D Shape
- New technique for studying human brain activity
- Next Generation Audio Coding
- Spherical multi-modal scene analysis
- Medical diagnostics for neonates in the developing world
- Electrical Impedance Tomography for stroke, biophysical monitoring and medical device design
- Impedance tomography for cardiac imaging: high speed tomography
- Novel Electrodes for rapid electrophysiological recording
- Binaural signal processing algorithms for hearing aids
Other opportunities with Professor Alistair McEwan
- Medical diagnostics for neonates in the developing world
- Electrical Impedance Tomography for stroke, biophysical monitoring and medical device design
- Impedance tomography for cardiac imaging: high speed tomography
- Novel Electrodes for rapid electrophysiological recording
- Implant electrode optimisation and neurolinguistics
- Subdivided electrodes to improve defibrillators and physiological measurements
- Electrical impedance modelling for implants
- Magnetic resonance electrical impedance tomography
- Development of a microwave catheter for cardiac ablation to treat ventricular tachycardia
- Resuscitation monitors for the neonatal intensive care uni (NICU)
- ARTIFICIAL INTELLIGENCE/MACHINE LEARNING ASSISTED NEWBORN CRITICAL CARE (VIRTUAL CRITICAL CARE MODELING)
- Mapping 2D Images to 3D Shape
- New technique for studying human brain activity
- Next Generation Audio Coding
- Spherical multi-modal scene analysis
- FPGA-based Low Latency Trading
- Floating Point FPGA Architectures
- Placement-aware Hardware Description Languages
- Scalable vision machines
- Modelling Parkinson's disease using control models
- Binaural signal processing algorithms for hearing aids
- FPGA-based low latency machine learning