3 accepted papers
Detecting small obstacles on the road ahead is a critical part of the driving task which has to be mastered by fully autonomous cars. In this paper, we present a method based on stereo vision to reliably detect such obstacles from a moving vehicle.
Visual understanding of complex urban street scenes is an enabling factor for a wide range of applications. Object detection has benefited enormously from large-scale datasets, especially in the context of deep learning. For semantic urban scene understanding, however, no current dataset adequately…
Reliable detection of obstacles at long range is crucial for the timely response to hazards by fast-moving safety-critical platforms like autonomous cars. We present a novel method for the joint detection and localization of distant obstacles using a stereo vision system on a moving platform. The ap…