Master Thesis - Visual Face anti-spoofing technology
Master Thesis - Visual Face anti-spoofing technology
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
Job Description
Job Title
Job Description
Category
Video analytics machine learning
Scope
Master Thesis 30 hp 2 students.
Background
In the realm of biometric verification technology the ability to differentiate between genuine users and spoof attempts is critical. Very simple methods such as printing images on paper or using phones and tablets can easily be exploited to deceive face recognition systems. This thesis aims to explore technology that detects whether a face in a video is real or a spoof focusing specifically on liveliness detection. The primary constraint is that only video sensor data will be utilized employing both computer vision and machine learning techniques.
Goal
This thesis aims to explore face anti-spoofing by examining spoofing attacks analyzing distinguishing features of real versus spoofed faces identifying benchmarking metrics proposing classification technologies for liveness detection and addressing data collection strategies.
Description
This thesis will encompass several key components:
1. Field Exploration of Face Anti-Spoofing
Investigate the various types of spoofing attacks that exist and their implications. The technological selection will be guided by the realism and complexity of potential attacks as successful spoofing could undermine the integrity of face verification systems.
2. Analysis of Characteristic Appearances
Examine the distinguishing features between real and spoofed faces. Identify useful information present in images supported by statistical data to illustrate these differences.
3. Benchmarking and Metrics
Investigate suitable benchmarks or metrics necessary for comparing different technologies and their effectiveness in liveness detection.
4. Proposing Classification Technologies
Recommend technologies capable of classifying the liveness of faces in video. Development and program execution will occur in a PC environment using offline materials.
OK I am interested! What do I do now
You are valuable to us how nice that you are interested in one of our proposals! There are a few things for you to keep in mind when applying.
- Applications are accepted in both Swedish and English and you apply via the proposal advert.
- The announced thesis is open only to students affiliated with a Swedish University/College either directly or via an exchange program.
- When the thesis proposal states that it includes two students working together we would like you to apply in pairs. In these cases send one application each but make sure to clearly state in your application who your co-applicant is. If you have any questions regarding this please do not hesitate to contact us.
- Please attach your CV and University/College grade summary.
Who to contact for any questions regarding the position!
Willie Betschart or Mikael Westlund
Type of Employment
Temporary Employment (Fixed Term)Posting End Date
Certain roles at Axis require background checks which means applicable verifications will be done in these recruitments. Notice will be provided before we take any action.
About Axis Communications
We enable a smarter safer world by creating innovative solutions for improving security and business performance. As a network technology company and industry leader we offer solutions in video surveillance access control intercom and audio systems enhanced by intelligent analytics applications.
With around 5000 committed employees in over 50 countries we collaborate with partners worldwide. Together we thrive in our friendly open and collaborative culture and inspire each other to think beyond the expected. United by our commitment to inclusion diversity and sustainability we consistently seek to develop our skills and way of working.
Lets create a smarter safer world
For more information about Axis please visit our website .
Listen to Get To Know Axis Podcast
Employment Type
Full-Time
