Avigilon Fortress Corporation

Objectvideo, Inc

Alarm.com Incorporated

Object Video Labs, LLC

Motorola Solutions, Inc.

Weihong Yin

Zhong Zhang

Peter L Venetianer

Alan J Lipton

Li Yu

Niels Haering

Donald Gerard Madden

Andrew J Chosak

Allison Beach

Gary W Myers

Paul C Brewer

Dana Eubanks

Zeeshan Rasheed

W Andrew Scanlon

Yongtong Hu

Péter L Venetianer

Matthew F Frazier

Himaanshu Gupta

David James Hutz

Benjamin Asher Berg

Christopher Silverman

Omar Javed

Andrew J Martone

James S Sfekas

John I W Clark

Geoffrey Egnal

Michael C Mannebach

Gang Qian

Haiying Liu

Andrew Scanlon

Dave Conger

Kyle Glowacki

Jeffrey A Bedell

Narayanan Ramanathan

Sima Taheri

Robert A Cutting

Donald Faraci

Adam Gordon

John Ian Wallace Clark

James Siemer

John Stanley

Ethan Shayne

James Morris

Kyoung-Jin Park

Steve Titus

Bruce Thompson

Amit Mistry

Pèter L Venetianer

Robert S Hastings

Liangyin Yu

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for monitoring events using a Virtual Inductive Loop system. In some implementations, image data is obtained from cameras. A region depicted in the obtained image data is identified, the region comprising lines spaced by a distance that satisfies a distance threshold. For each line included in the region: an object depicted crossing the line is determined whether to satisfy a height criteria indicating that the line is activated. In response to determining that an object depicted crossing the line satisfies the height criteria, an event is determined to have likely occurred using data indicating (i) which lines of the lines were activated and (ii) an order in which each of the lines were activated. In response to determining that an event likely occurred, actions are performed using at least some of the data.

Vehicular access control based on virtual inductive loop

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for retroactive event detection. The methods, systems, and apparatus include actions of obtaining an image captured by a camera at a current time, determining that the image depicts a change in a region from a previous image captured by the camera at a previous time, determining, based on determining that the image depicts the change in the region, whether the change depicted in the image is of a known object type, determining, based on the determination that the change depicted in the image is of a known object type, whether the change does not correspond to a previously detected event, and determining, based on the determination that the change does not correspond to a previously detected event, whether the images captured by the camera between the current time and the previous time depict an event.

Event detection in video surveillance

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for group identification and monitoring. The methods, systems, and apparatus include actions of determining, using one or more first frames of a video sequence, that two people each of whom is depicted in at least one of the first frames satisfy a grouping criteria that indicates that the two people should be grouped for video analysis, determining, using one or more second frames of the video sequence at least some of which were captured after the one or more first frames and which depict at least one of the two people, that the two people satisfy a degrouping criteria that indicates that the two people should not be grouped for video analysis, determining that a physical distance between the two people violates a distance criteria, and providing an alert that the distance criteria is violated.

Group identification and monitoring

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

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for adjusting of video analytics rules for camera movement. The methods, systems, and apparatus include actions of obtaining a rule that specifies a first set of coordinates applied to a first set of images from a camera, determining an amount and direction of movement of the camera after the rule was obtained, determining, based on the amount and direction of movement of the camera, a second set of coordinates applied to a second set of images captured after the camera moved.

Automatic adjusting of video analytics rules for camera movement

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for finding lost objects. In some implementations, an unassociated object that appeared in a video from a property is identified. Known entities for the property are identified. A number of times that the known entities appeared in videos from the property is obtained. An order to display the known entities for the property based on a number of times that the known entities appeared in videos from the property are determined. An indication that the unassociated object is associated with a particular entity of the known entities is received. An image of the unassociated object from the video in association with the particular entity of the known entities is stored.

Cross-video object tracking

Methods, systems, and apparatus, including computer programs encoded on a storage device, are disclosed. A system includes one or more processors and one or more computer storage media storing instructions that are operable, when executed by the one or more processors, to cause the one or more processors to perform operations comprising: obtaining, by the system, video of a scene captured by a camera; determining a likelihood that the camera will be tampered with based on the video of the scene; determining that the likelihood that the camera will be tampered with satisfies criteria; and transmitting data generated from the video.

Notifications for camera tampering

Methods and systems including computer programs encoded on a computer storage medium, for receiving, from a camera, an image in which the camera detected a particular event based on a first set of camera settings, determining, from the image, that the image is a false positive as the camera falsely detected the particular event, determining that a number of images uploaded by the camera that are false positives satisfies a camera setting generation criteria, and in response, generating a second set of camera settings and providing the second set of camera settings to the camera.

Dynamic calibration of surveillance devices

Methods and systems including computer programs encoded on a computer storage medium, for receiving, from a camera, a set of images in which the camera detected a particular event based on a first set of camera settings, determining that false detections in the set of images made by the camera based on the first set of camera settings were caused by localized errors, and in response, generating a second set of camera settings based on the localized errors and providing the second set of camera settings to the camera.

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

Systems, methods and computer-readable media for creating and using video analysis rules that are based on map data are disclosed. A sensor(s), such as a video camera, can track and monitor a geographic location, such as a road, pipeline, or other location or installation. A video analytics engine can receive video streams from the sensor, and identify a location of the imaged view in a geo-registered map space, such as a latitude-longitude defined map space. A user can operate a graphical user interface to draw, enter, select, and/or otherwise input on a map a set of rules for detection of events in the monitored scene, such as tripwires and areas of interest. When tripwires, areas of interest, and/or other features are approached or crossed, the engine can perform responsive actions, such as generating an alert and sending it to a user.

Systems and methods for video analysis rules based on map data

Embodiments relate to systems, devices, and computer-implemented methods for performing automated visual surveillance by obtaining video camera coordinates determined using video data, video camera metadata, and/or digital elevation models, obtaining a surveillance rule associated with rule coordinates, identifying a video camera that is associated with video camera coordinates that include at least part of the rule coordinates, and transmitting the surveillance rule to a computing device associated with the video camera. The rule coordinates can be automatically determined based on received coordinates of an object. Additionally, the surveillance rule can be generated based on instructions from a user in a natural language syntax.

Systems and methods for automated visual surveillance

Growing community of inventors

Great Falls, VA, United States of America

Weihong Yin