Internship in Face Oriented Computer Vision
Location : Acep TryLive, 88 rue Jouffroy d’Abbans 75017 Paris
Departement : R&D
Internship : Last year of study of engineering program or master 2
Duration : 6 months
Dates : to be defined
Remuneration : Yes
Since 20 years Acep (http://www.opticvideo.com) has been offering a range of high added-value measurement solutions, developed upstream with lens manufacturers leaders, to respond to the eyewear customers’ needs and to the specific features of the latest-generation lenses. Acep is present in all continents and is a leader in its market.
Its subsidiary Acep TryLive (http://www.trylive.com) is specialized on the solutions based on augmented reality and computer vision. Its main product enables virtual try-on of glasses and serves for retail, e-commerce, mobile commerce and brand marketing. Building on over a decade of augmented reality experience and unique patented technologies, TryLive enables enhanced and social shopping experiences both at home, in store and online.
Intern will be integrated in the R&D team of Acep Trylive and will be guided by the specialist of real-time image processing, computer vision and machine learning.
The internship will focus either on the development of algorithms or on research, evaluation and integration of external technology. Possible topics of the internship are :
- Determination of 6D face pose from 2D markers
- Improvement of face 6D tracking on pre-recorded image sequences
- Determination of 3D face geometry from 6D tracking and 2D markers
- Development of face tracking automatic tests system
The main steps will be :
- Analyses of the potential solutions : bibliography research, research of the existing technology
- Algorithms development or integration of the technology
- Development of the evaluation system of the results
- Evaluation of the results
These topics may vary depending on your skills and interests. You’ll get the opportunity to work on real projects focused on the improvement of the Acep TryLive solution :
- Improve robustness and precision
- Increase the quantity of information extracted from the image
- Improve the user experience
Development will be restricted by the real-time constraints and ability to integrate on multiple platforms.
- Last year of study of engineering degree or master 2 in computer science with specialization in computer vision and/or image processing and/or machine learning
- Ability to handle a variety of software, source code, APIs
- Knowledges of C/C++ (and environment MS Visual Studio), Python
- Motivation, Adaptability, Creativity & Inventiveness
- Strong interest in the fields of augmented reality and ability to work in an international environment