Avigilon Fortress Corporation

Objectvideo, Inc

Yongtong Hu

Zhong Zhang

Alan J Lipton

Weihong Yin

Li Yu

Peter L Venetianer

W Andrew Scanlon

Andrew J Martone

Niels Haering

Andrew J Chosak

Gary W Myers

Péter L Venetianer

Paul C Brewer

Robert A Cutting

Methods and systems are provided for monitoring a point of sale (POS) transaction. Operations performed by the methods and systems include generating POS primitives by processing non-video data of a transaction recorded at POS terminal. The operations also include generating video primitives by processing video data of the transaction recorded at the POS terminal. The operations further include determining that the transaction comprises an exceptional transaction by comparing the non-video data and/or the video data to exceptional transaction rules. Additionally, the operations include determining that the exceptional transaction comprises a verified exceptional transaction by generating a video event based on the video primitives and a corresponding video rule.

Intelligent video verification of point of sale (POS) transactions

A video surveillance system is set up, calibrated, tasked, and operated. The system extracts video primitives and extracts event occurrences from the video primitives using event discriminators. The system can undertake a response, such as an alarm, based on extracted event occurrences.

Video surveillance system employing video primitives

A method of monitoring a point of sale (POS) transaction including: receiving non video data regarding the POS transaction; defining exceptional transaction rules based at least on predetermined non video POS data events; inferring a potentially exceptional transaction based on a corresponding exceptional transaction rule and the received POS non video data; and verifying the inferred potentially exceptional transaction with video data regarding a corresponding POS transaction.

A system for video monitoring a retail business process includes a video analytics engine to process video obtained by a video camera and generate video primitives regarding the video, A user interface is used to define at least one activity of interest regarding an area being viewed, each activity of interest identifying at least one of a rule or a query regarding the area being viewed. An activity inference engine processes the generated video primitives based on each defined activity of interest to determine if an activity of interest occurred in the video.

Video analytics for retail business process monitoring

Non video data regarding a point of sale (POS) transaction is received. POS primitives are generated based on the received non video POS data. Video data regarding a corresponding POS transaction is received. Video primitives are generated based on the received video data. An exceptional transaction is inferred based on a corresponding exceptional transaction rule and at least one of the generated POS primitives or video primitives.

A technique for video processing includes: receiving video from a scene; detecting moving pixels in the video; detecting line segments or motion blocks in the video based on the detected moving pixels; identifying targets in the video based on the detected line segments or motion blocks; tracking targets in the video based on the identified targets; and managing the tracked targets in the video.

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Herndon, VA, United States of America

Yongtong Hu