Machine Learning

BIO-PERCEPTION - Next generation of smart vision systems for real-time processing with bio-inspired sensors

Our goal for this project is to set up the basis for a new generation of smart autonomous agents that are able to carry out 3D perception in real-time, using biologically-inspired vision sensors. These sensors independently processed all pixels and only trigger changes in the scene (events) in the case a substantial difference in the intensity luminance happens over time for a specific location (this happens only at object contours and textures). This allows for the reduction of the transmission of redundant information and hence, the data bandwidth.

Contour detection and proto-segmentation with event sensors

This project presents an approach to learn the location of contours and their border ownership using Structured Random Forests on event-based features. The contour detection and boundary assignment are demonstrated in a proto-segmentation application