How to ensure quality and accuracy in Pix4Dmapper - Pix4Dmapper Video Tutorial 10

In this Pix4Dmapper Video Tutorial 10 section, Marc Degroseilliers from Pix4D's technical support team discusses four methods to ensure quality and accuracy in projects created in Pix4Dmapper. The first method is visual inspection, where users check the point cloud for correct feature placement and model curvature. If needed, they can densify the point cloud and examine misaligned patches. Secondly, users can utilize the quality report for assessing project quality. Green checkmarks signify good results, while red ones indicate issues. Pix4D provides a quality report help support page for troubleshooting. Thirdly, the graphics in the quality report offer quick project overviews, including original and optimized camera position alignment and estimated project overlap. Well-aligned optimized camera positions and homogeneous, green-colored estimated overlap indicate good project quality. Lastly, version 2.2 of Pix4Dmapper introduced uncertainty ellipses, indicating the software's confidence in camera positions and orientations. Projections in the raycloud allow inspecting specific areas, and checkpoints with precise geolocation data provide unbiased accuracy estimates.

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