Luis M. Bergasa

TL;DR: A deep architecture that is able to run in real time while providing accurate semantic segmentation, and a novel layer that uses residual connections and factorized convolutions in order to remain efficient while retaining remarkable accuracy is proposed.

TL;DR: A non-intrusive prototype computer vision system for real-time monitoring driver's vigilance based on a hardware system, for real time acquisition of driver's images using an active IR illuminator, and their software implementation for monitoring some visual behaviors that characterize a driver's level of vigilance.

TL;DR: A components-based learning approach is proposed in order to better deal with pedestrian variability, illumination conditions, partial occlusions, and rotations and suggest a combination of feature extraction methods as an essential clue for enhanced detection performance.

TL;DR: DriveSafe is the first app for smartphones based on inbuilt sensors able to detect inattentive behaviors evaluating the quality of the driving at the same time and represents a new disruptive technology because it provides similar ADAS features that found in luxury cars.

TL;DR: The design is completed with acoustic feedback to assist visually impaired users while approaching obstacles and audio bone conducting technology is employed to play these sounds without interrupting the visually impaired user from hearing other important sounds from its local environment.