Abstract
Automated measurement of the relative pose between a crane borne curtain wall module and its installation location on the side face of a high-rise building can be applied to increase the safety and efficiency of crane operations though informing the action required to achieve alignment. However, the detection and measurement tasks are challenging because the construction site is large, unstructured, and highly dynamic. This article introduces a markerless computer vision measurement algorithm and a practical implementation, which uses a forward-facing infrared camera attached to the crane spreader. The algorithm self-verifies the measurement against known information so that it can fail safely instead of returning a malformed measurement. The algorithm is experimentally validated in challenging lighting conditions. The window frame segmentation achieved Fβ=0.59. Overall, the algorithm returned 71% successful and 0 malformed measurements.
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