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The robust detection of obstacles, on a given road path by vehicles equipped with range measurement devices represents a requirement for many research fields including autonomous driving and advanced driving assistance systems. One particular sensor system used for measurement tasks, due to its known accuracy, is the LIDAR (Light Detection and Ranging). The commercial price and computational intensiveness...
Depth estimation of the surrounding environment using a stereoscopic camera setup is an important and fundamental research topic in computer vision. Due to its running time and quality performance in real situations the semi global matching algorithm is often used. The biggest disadvantage of the semi global approach is its large memory footprint. On the other hand, block matching stereo is leaner...
Stereo cameras are a viable solution for reconstructing 3D scenes and are well suited for advanced driver assistance systems, autonomous driving and robotics applications. Modern stereo reconstruction algorithms offer good results, but require very much memory and their real time capabilities are limited on modern day processors. On the other hand, local window aggregation algorithms have a small...
In the automotive industry the issue of safety remains a major priority. This aspect is not focused just on the driver but also on the other participants of the traffic like the pedestrians. This paper describes a pedestrian detection system where three different classification methods are used for detecting pedestrians with a far infrared camera. The three methods are tested and compared on variable...
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