Fachbereich Informatik

Ahmet Firintepe

(DFKI, Prof. Stricker)
hosted by PhD Program in CS @ TU KL

"Deep learning based visual head and glasses tracking"

( MPI-SWS talk in Kooperation mit dem Fachbereich Informatik)

Deep learning approaches show remarkable results and advance the state of the art to solve future problems with challenging requirements. For the head-pose estimation problem, current deep-learning techniques show high accuracy.Dataglasses can be worn like typical glasses, but allow to show virtual content directly in front of the wearer’s eyes. A convincing superimposition during driving requires to track the orientation and the position of the dataglass inside the car, which is challenging due to high accuracy and low latency requirements. Therefore a deep learning-based pose and position estimation algorithm shall increase the accuracy via a combination of head pose estimation and object-based, i.e., glasses-based, tracking using visual data.

Bio:


Time: Monday, 03.02.2020, 15:30
Place: 48-680
Video: