Predicting inventory events using semantic diffing

This invention describes a system that watches a physical area, like a store shelf or a warehouse, using several cameras with overlapping views. It works by first identifying and ignoring people in the camera's view, then looking for changes in the background, such as an item appearing or disappearing. The system can also link these inventory changes to the specific person who caused them, using advanced computer vision techniques like neural networks to recognize these changes.