2D refreshable tactile displays for automatic audio-tactile graphics



Translating graphical information to a tactile display is a difficult process requiring vast expert knowledge due to differences in visual and tactile perception and limitation of devices This project will first focus on developing guidelines and rules on how to map different graphical content types to tactile domain, considering insight into tactile processing. To analyze and extract the most relevant information from graphics, state of the art image processing techniques will then be used, such as automatic classification of selected graph types using state of the art machine learning techniques.

Expected Results

Automatic generation of audio-tactile graphics with state-of-the-art machine learning techniques.

Planned secondments

ICL: to learn predictive coding

ULUND: to learn tactile encoding and neural recording


Host institution: Karlsruhe Institute of Technology

Enrolments (in Doctoral degree): Karlsruhe Institute of Technology


Rainer Stiefelhagen, Klaus-Peter Hars