Computer Vision based inspection on post-earthquake with UAV synthetic dataset

Earthquakes are sudden and violent disasters that cover huge areas of land in a very short period of time. They have been known to mankind since ancient times and invariably pose one of the most serious threats to the lives of people concentrated in large cities. The scale of their destructive power can be seen in the number of nearly two million earthquake victims in the 20th century alone [1], or in the most devastating events, which could claim up to nearly a million lives [2]. At the same time, the map of seismically active areas largely overlaps with densely populated areas, particularly in North America, Europe and Asia [3], which focuses researchers on this type of hazard and methods of its mitigation. Studies conducted to date have assessed the effects of earthquakes both in terms of the impact on housing and infrastructure, and the performance of public services in repairing damage or improving traffic flow in the affected area [4, 5]. These works have led to concepts of cities in which such events will no longer have a critical impact on the lives of residents, but with the cost of monitoring the condition of structures even after seemingly harmless, small earthquakes to take corrective action immediately after damage occurs [6]. This, however, requires the use of modern methods of construction monitoring to reduce the labor intensity of the entire process, without which the end goal is impossible to achieve. In this paper, we present our step towards building autonomous systems that can bring this goal closer.