Capture Body Anthropometrics using a Smart Device
Location: Sydney, NSW
Duration: 5 months
SmartFit Technologies has created a set of innovative systems to accurately measure multiple features of the human body with a Smart device. Our engineers have developed our core technology using machine prediction and computer vision algorithms to analyse images of the human body and return accurate anthropometrics to the user.
This start-up has a working prototype of the core technology and is now seeking a Researcher with a background in at least one of the following areas:
- Multiple view geometry
- 3D reconstruction from images & sensors
- Mesh processing and other computer 3D vision related fields.
Research to be Conducted
- Research latest academic literature on applications of deep learning / 3D vision to human anthropometric modelling.
- Explore the available 3D models/mesh of human images data set and propose ways to leverage them to improve accuracy in the existing solution.
- Research and design prototype to compute body measurements from 2D images.
- Design landmark detection algorithm to detect key feature points (bust, waist, hip etc) in human images.
If you’re a PhD student and meet some or all the below we want to hear from you. We strongly encourage women, indigenous and disadvantaged candidates to apply:
Experience in one of the following :
• Multiple view geometry, 3D reconstruction from images & sensors, Mesh processing and other computer 3D vision related fields.
• Experience in applying machine learning and deep learning techniques to computer vision.
• Ability to prototype code from research papers.
Experience working in
• Python and C#
The objective is to :
• improve the accuracy of body measurement component to 95% i.e. 95% of the cross validated set images to have individual measurement error within 5mm.
• design landmark detection algorithm to replace the existing heuristics/hand crafted approach of feature point detection.
The intern will receive $3,000 per month of the internship, usually in the form of stipend payments.
It is expected that the intern will primarily undertake this research project during regular business hours, spending at least 80% of their time on-site with the industry partner. The intern will be expected to maintain contact with their academic mentor throughout the internship either through face-to-face or phone meetings as appropriate.
The intern and their academic mentor will have the opportunity to negotiate the project’s scope, milestones and timeline during the project planning stage.
27 November 2019
APR – 1270