Project description:

Being constrained to keep a straight face should no longer be a condition for a well-performing face recognition system. IDform proposes to robustly identify people from their faces in full dynamic conditions. The idea is to build on the success of today’s best performing face systems that use deep learning; however, instead of chasing the hugest datasets, the strategy is to use efficient facial models that can provide stable statistical information.

• Starting date: 01/05/2018
• Duration: 42 months
• Funding source: FNR CORE PPP
• Researchers: Dr. Anis Kacem, Kseniya Cherenkova, Prof. Djamila Aouada (PI)
• Partners: Artec3D