System and method for operating room human traffic monitoring

A computer system for monitoring traffic in an operating room, the system comprising:

• at least one processor;
• memory in communication with said at least one processor;
• and
• software code stored in said memory, which when executed at the at least one processor causes said system to:
• receive video data of an operating room, the video data captured by a camera having a field of view for viewing movement of a plurality of individuals in the operating room during a medical procedure;
• store an event data model including data defining a plurality of possible events within the operating room;
• process the video data to track movement of objects within the operating room, the objects including at least one body part, and the processing using at least one detector trained to detect a given type of the objects;
• and
• determine a likely occurrence of one of the possible events based on the tracked movement.

A non-transitory computer-readable storage medium storing machine executable instructions which when executed by a processor, cause the processor to perform a method for traffic monitoring in an operating room, the method comprising:

• receiving video data of an operating room, the video data captured by a camera having a field of view for viewing movement of a plurality of individuals in the operating room during a medical procedure;
• storing an event data model including data defining a plurality of possible events within the operating room, the event data model trained to utilize a total number of people in the operating room as a conditioning variable, and trained using a data set of training frames from training procedures used to update a set of weight parameters representing a trained event data model;
• processing the video data using one or more trained object-tracking models configured to track movement of objects within the operating room, the objects including at least one body part, and the processing using at least one detector trained to detect a given type of the objects, the movement of the objects processed to estimate changes to a total number of people in the operating room based on the at least one body part in the video data at a particular time and to record a timestamp when the estimated change occurs;
• and
• at a particular time or duration of time, determining a likelihood of occurrence of one of the possible events based on the tracked movement and by processing the estimated total number of people in the operating room as the conditioning variable against the trained event data model;
• and
• generating a data output representative of the likelihood of occurrence of one of the possible events.