We tackle the problem of semi-automatic road tracking in aerial photos. Our solution to this human-computer interaction problem is to provide a learning approach that integrates naturally input from human experts with automatic tracking of roads. More specifically, our system learns an ensemble of road predictors from human inputs and uses them to further track a road, alerting the human expert when novel situations are encountered. The proposed approach is shown to outperform existing manual and semiautomatic methods.
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