Self-calibrating cross-camera homography for real-time ghost prediction in multi-camera person tracking

The problem: In multi-camera tracking, when camera A loses track of a person but camera B still sees them, naive approaches extrapolate pixel coordinates linearly. This fails immediately because cameras have completely different coordinate systems. A person at pixel (400, 300) on camera B might be at (800, 500) on camera A, depending on relative position and angle. Approach: When both cameras simultaneously observe the same person (matched via 64-dim HSV appearance descriptors, L2-normalized), the system learns the geometric transformation between them in real-time, enabling accurate prediction of where the person will appear when switching camera views.