In terms of methods for measuring the distance between two points in space, field measurements have limitations due to time-space constraints. Moreover, methods using 3D scanners require high costs and long working hours. In order to improve such limitations, this study proposes an algorithm of automated pixel correspondence searching method using CNN (Convolutional Neural Network) and Z-NCC (Zero-Mean Normalized Cross-Correlation). The proposed algorithm applies a method where the user selects one pixel from a photo among multiple photos from the field after aligning the photos by position using SfM (Structure from Motion) and then automatically calculates the corresponding pixel from another photo using CNN and Z-NCC to triangulate the depth of the selected pixel.
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