Fast Computation of Dense and Reliable Depth Maps from Stereo Images

Abstract

Modern cars and robots act and interact more and more autonomously. Therefore they are equipped with a set of various sensors to monitor their surroundings. Depending on the application of such devices, different aspects of the measurement data are relevant and have to be extracted during post processing. The evenness of the movements depends on the sampling rate of the sensors. Yet for close interaction with people a very reliable information about the environment is necessary.