The study aimed to find the best photogrammetry technique that balances accuracy with the number of photos required. The optimization process identified a top-performing gene set, referred to as 22FBG3-14. However, when further reducing the number of photos in this gene set, there were noticeable increases in inaccuracies in volume, indicating that 22FBG3-14 might be a local optimum. Given the vast number of possible gene sets, it's challenging to determine if the identified solution is a global or local optimum, and finding the true global optimum would demand substantial computational resources.