In our current camera pose UX/UI, while the direct approach for adjusting camera parameters based on user interaction works effectively for initial correspondence points, it becomes increasingly challenging as more points are added. The system becomes over-constrained, leading to potential conflicts and inaccuracies, particularly when dealing with non-linearities and distortions. This challenge limits the effectiveness of real-time feedback and poses a risk to the overall user experience.
The proposed solution involves implementing a hybrid approach that combines the initial direct "equations of motion" method for quick and intuitive adjustments with a secondary fine-tuning step using the Levenberg-Marquardt algorithm. This two-phase approach will allow for real-time responsiveness during early interactions, while ensuring accuracy and stability as more correspondence points are added. The system will dynamically switch to the optimization-based method once the number of points exceeds the threshold where the system becomes over-constrained. This ensures that the camera parameters are finely tuned without sacrificing the user experience.