Preprocessing for Monocular or Stereo Computer Vision Systems, with Emphasis on SFM Algorithms

Traditional Structure from Motion (SFM) systems face computational bottlenecks due to quadratic processing complexity. This paper presents a bio-inspired frame selection approach combining compound eye visual systems with swarm intelligence algorithms based on honeybee foraging behavior. The methodology implements scout bees for exploration, worker bees for evaluation, and waggle dance communication. Experimental validation on KITTI datasets demonstrates 50-75% reduction in processing time while maintaining reconstruction quality, with improved point density per frame and lower reprojection errors compared to sequential processing methods.