Anomalous stationary object detection and reporting

This invention uses a camera to watch a scene and identify objects that stop moving and stay still for a certain period. It then creates a special map based on the movement of other objects in the scene. Using this map and the object's stationarity, it calculates how unusual it is for that object to be stationary in that specific location, reporting it if rare enough.

Why it matters: Filed before advanced real-time object detection and anomaly detection models became widely accessible. Modern ML frameworks make building and deploying the learning model for rareness scoring significantly easier.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedSoftware logic, machine learning, video processing

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