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
This project shows the development of various classification tasks in static and dynamic environments with the Baxter robot based on color, using also a conveyor where pieces are transported to be classified in real time.
This project presents an FPGA architecture for the computation of visual attention based on the combination of a bottom-up saliency and a top-down task-dependent modulation streams. The target applications are ADAS (Advanced Driving Assistance Systems), video surveillance, or robotics.
Fine-grain pipelined and superscalar datapath to reach high performance at low working clock frequencies with FPGAs. The final goal is to achieve a data-throughput of one data per clock cycle. We show implementations of optical flow, disparity, and low-level local features