CHOW-SLAM: Compact Hybrid Representation with Complementary Overlap Window Optimization for RGB-D SLAM
This work proposes CHOW-SLAM, a dense RGB-D SLAM framework that explicitly constructs these complementary spatial and temporal constraints, and proposes a complementary overlap-window strategy to prevent optimization from being dominated by short-term overlap or weakly related historical observations.