[visionlist] Second call for expressions of interest: 2 PhD positions at the University of Technology, Sydney, Australia

Perceptual Imaging Laboratory, School of Computing and Communications, Faculty of Engineering and Information Technology, University of Technology, Sydney is seeking
expressions of interest from students wishing to undertake PhD studies on the topics listed below.

Eligibility: Bachelors degree with honours in computer science, psychology, vision science or related field. Prior experience in colour science and/or visual psychophysics
is desirable. Programming proficiency in MATLAB, C, C++, R or Python is an advantage. Australian and International students are welcome to express interest.

Prospective applicants should include a CV, a short research statement describing the topic that the candidate is interested in and why they feel that they are a good
match for the topic. The potential candidate should also provide a date of availability for interviewing and names and contact information of at least two references.

Please send expressions of interest to A/Prof Stuart Perry (Stuart.Perry@uts.edu.au).

Degree: PhD

Supervisors: A/Prof Stuart Perry (UTS)

Co-supervisor: Dr Juno Kim (UNSW)

Project Description: Perceptually-accurate simulation of real surfaces and materials in virtual environments (joint project with School of Optometry and Vision Science,
University of New South Wales):

An exciting opportunity is available to undertake a PhD conducting research on a cross-institutional collaboration in the field of surface and material appearance. Material
appearance is the vivid perceptual experience we have of different material properties when we look at images (e.g., 3D shape, colour, gloss, lightness/albedo). Research into graphics and visual reality aims to simulate interactions of light with surfaces
to generate these material experiences in artificial environments, both in real-time and as realistically as possible. Much of the complexity in light’s interaction with opaque objects can be simulated using computational models, such as a BRDF. Although BRDF
information is generally captured using highly specialised equipment, this equipment is usually not well-suited to the problem of scanning real-life 3D objects. This is because many real-life objects have complicated BRDFs and may even deviate beyond the scope
of these models (e.g., when objects are semi-opaque). Hence, collecting accurate material appearance for real 3D objects is still a potentially complicated problem.

This project is primarily concerned with the collection of material appearance information from scans of real objects. Current techniques attempt to bring together multiple
image captures to collect sufficient information to resolve a physical model of surface reflectance, such as a micro-facet model. However, as material appearance is directly related to how humans perceive materials, this project will also use psychophysical
experimentation to elucidate the fundamental dimensions of model parameters that are necessary to maximise the efficient capture and simulation of physical surface properties.

 

Degree: PhD

Supervisors: A/Prof Stuart Perry (UTS)

Co-supervisor: Dr Juno Kim (UNSW)

Project Description: Light-Field Photography Enhanced 3D Object Scanning (joint project with School of Optometry and Vision Science, University of New South Wales):

An exciting opportunity is available to undertake a PhD conducting research on a cross-institutional collaboration in the field of surface and material appearance. Light-field
cameras such as the Lytro ILLUM capture not only the intensity of light striking the sensor, but also the angle of incidence of the light. This information can be used to reconstruct depth information, change focal point post-capture, and change viewpoint
post-capture. The project is to develop algorithms for 3D shape capture technologies using light-field camera systems. In particular, to develop 3D capture methods that can quantify and capture material appearance properties such as colour changes with angle
or gloss characteristics, by making use of the unique properties of the additional information present in light-field images. This project would involve developing algorithms that compensate for the effects of errors in depth estimation across different material
types and improve the accuracy and reliability of the recovery of 3D shape and material properties using light-field cameras.

 

Stuart Perry

Associate Professor, School of Computing and Communications

Faculty of Engineering and Information Technology | University of Technology Sydney

Building 11, Level 8, Room 217, 81 Broadway, Ultimo NSW 2007 (PO Box 123)

UTS CRICOS Provider Code: 00099F
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