Samenvatting
Data-driven approaches to constructing context aware driver assistance systems require large annotated databases of automobile sensor data. Manually annotating such large databases is costly and time-consuming. A semi-automatic annotation tool for this purpose that uses Random Forests as bootstrapped classifiers is presented. The tool significantly reduces the manualannotation effort and thus enables the user to verify automatically generated annotations, rather than annotating from scratch. For the covering abstract see E134653.