Avigilon Fortress Corporation

Objectvideo, Inc

Motorola Solutions, Inc.

Li Yu

Zhong Zhang

Peter L Venetianer

Alan J Lipton

Weihong Yin

Haiying Liu

Himaanshu Gupta

Niels Haering

Paul C Brewer

Andrew J Chosak

W Andrew Scanlon

Yongtong Hu

Khurram Hassan-Shafique

Zeeshan Rasheed

Péter L Venetianer

Dana Eubanks

Andrew J Martone

Omar Javed

John I W Clark

Steve Titus

Donald Gerard Madden

Geoffrey Egnal

Geoffrey R Taylor

James Morris

Xiao Chun Cao

Bruce Thompson

Amit Mistry

Wei Hong Yin

Gary W Myers

Robert A Cutting

Mun Wai Lee

Pèter L Venetianer

Liangyin Yu

Kelly Schomburg

Asaad Hakeem

A method and system using face tracking and object tracking is disclosed. The method and system use face tracking, location, and/or recognition to enhance object tracking, and use object tracking and/or location to enhance face tracking.

Object tracking and best shot detection system

A sequence of video frames of an area of interest is obtained. A first background model of the area of interest is constructed based on a first parameter. A second background model of the area of interest is constructed based on a second parameter, the second parameter being different from the first parameter. A difference between the first and second background models is determined. A stationary target is determined based on the determined difference. An alert concerning the stationary target is generated.

Stationary target detection by exploiting changes in background model

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 even occurrences from the video primitives using event discriminators. The extracted video primitives and event occurrences may be used to create and define additional video analytic rules. The system can undertake a response, such as an alarm, based on extracted event occurrences.

Video analytic rule detection system and method

Provided is a computer-implemented method for processing one or more video frames. The meth can include generating, by a processor, a change in value of one or more pixels obtained from the one or more video frames; classifying, by the processor, the change in value of the one or more pixels to produce one or more classes of the change in value of the one or more pixels, wherein the one or more classes include one or more of a stationary target, a moving target, a target insertion, a target removal, or a local change; and constructing, by the processor, a listing of detected targets based on the one or more classes.

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 system for detecting behavior of a target may include: a target detection engine, adapted to detect at least one target from one or more objects from a video surveillance system recording a scene; a path builder, adapted to create at least one mature path model from analysis of the behavior of a plurality of targets in the scene, wherein the at least one mature path model includes a model of expected target behavior with respect to the at least one path model; and a target behavior analyzer, adapted to analyze and identify target behavior with respect to the at least one mature path model. The system may further include an alert generator, adapted to generate an alert based on the identified behavior.

Video processing system using target property map

A video surveillance system may include at least one sensing unit capable of being operated in a scanning mode and a video processing unit coupled to the sensing unit, the video processing unit to receive and process image data from the sensing unit and to detect scene events and target activity.

Scanning camera-based video surveillance system

A sensing device includes: a video imager to obtain a video; a processing unit to receive and process the video from the video imager; and a communication channel to output non-imagery signals.

Video imagery-based sensor

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Herndon, VA, United States of America

Li Yu