Coactive Design of Human-machine Collaborative Damage Assessment Using UAV Images and Decision Trees

Abstract

Damage assessment is urgently needed for analyzing how badly a building has been destructed by weapons or by other disasters. However, it is dangerous for humans to go to the destructed area and assess the situation in real-time. In this paper, we propose a human-machine collaborative approach for the damage assessment task using UAV images. Specifically, we use the coactive design method to carry out the interdependence analysis of human and machine in each subtask. After matching the scenes before and after the damage, appearance differences of the target building are captured by ratio method. Then, we use a pre-trained decision tree to evaluate the degree of functional damage of the building. We demonstrate the effectiveness of the proposed method with images captured by a UAV in real-world environments.