We’ve conducted tests comparing datasets captured with the DJI Mavic 3E RTK using Smart Oblique and standard oblique modes. Each dataset comprised approximately 1,500 images of a construction site. Notably, processing the Smart Oblique dataset in PIX4Dmatic required at least five times longer than the standard oblique dataset.
We are aware that oblique imagery can increase processing times due to the complexity and volume of data. However, the substantial difference observed raises concerns about potential inefficiencies or issues specific to Smart Oblique imagery.
Could anyone provide insights into why Smart Oblique imagery might cause such a significant increase in processing time? Did we do something wrong? Are there recommended settings or workflows to optimize the processing of Smart Oblique datasets in PIX4Dmatic? Smart oblique reduces the flight time dramatically, and we wish to use this mode if possible.
I am also experiencing long process times as well as wrong camera calibration. I suspect it is because the orientation angles (yaw,pitch, roll) are those from the drone and not the gimbal, I am still waiting for user inputs and a response for support…
Months are already gone without even an answer. Hello support??? Whats the workflow here?
Sorry for the delay in answering. Indeed, this does not seem to be handled well today and we need to look into that. Are all Smart Oblique flights problematic or does it happen in specific cases for you? Would you be willing to share some problematic datasets with us, maybe even with the analysis you’ve made? This could speed up the process to find a solution.
@drones6 feel free to create a ticket in case there is an urgent request, you can click on Pixie
and from there it’s possible to directly reach out to a support agent.
@Pierangelo_Rothenbuhler - I just messaged you a link to a smart oblique dataset for this site - District Line Rd - Chandler - NIRA
This was done with the DJI M3E. I have other datasets available from the M3E, as well as the M300+P1 if needed.
Thanks
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Thanks @Derrick_Westoby1, shared with the team for further investigation
