Intelligent Damage Assessment for Post-Earthquake Buildings Using Computer Vision and Augmented Reality

The most negative effects caused by earthquakes are the damage and collapse of buildings. Seismic building retrofitting repair can effectively reduce impact on post-earthquake priority to construction after being damaged an earthquake is perform assessment seismic traditional method mainly based visual inspection, which highly subjective has low efficiency. To improve intelligence assessments for buildings, this paper proposed using CV (Computer Vision) AR (Augmented Reality). Firstly, a fusion mechanism method. Secondly, CNN (Convolutional Neural Network) algorithm gray value theory used determine information Then, be visually displayed according information. Finally, case seismic-reinforced concrete frame beams verify feasibility effectiveness