Application of SIFT operator with binocular vision fusion in Building engineering measurement

With the increasing demand for higher accuracy and reliability in the field of engineering measurement, traditional methods have shown a series of problems when facing complex scenarios and precision measurement tasks. Therefore, a scale invariant feature transformation engineering measurement method integrating binocular vision is proposed. This study focuses on binocular vision three-dimensional dimension measurement, using two-dimensional chessboard for monocular and binocular calibration to obtain internal and external reference information. At the same time, the scale invariant feature transformation algorithm has been simplified, combined with epipolar geometry to improve matching performance. The experiment showed that the improved scale invariant feature transformation algorithm achieved a matching accuracy of 97%. After fusing binocular vision, the close range matching was improved to 98%, the matching time was reduced to 1.8 seconds, and the number of feature points was reduced to 24. In distance measurement, the minimum error for planar targets was 0.25%, the maximum error for curved targets was 1.08%, and the overall maximum error percentage was 2.24%. The scale invariant feature transformation operator that integrates binocular vision has achieved significant results in engineering measurement, showing higher accuracy and reliability in three-dimensional dimension measurement compared to traditional methods. This innovative method is expected to improve measurement accuracy and reliability, providing a more accurate and feasible solution for three-dimensional dimension measurement in the engineering field.