Avigilon Corporation

Motorola Solutions, Inc.

Yanyan Hu

Mahesh Saptharishi

Pietro Russo

Kevin Piette

Moussa Doumbouya

Bo Yang Yu

Peter L Venetianer

Lu He

Shaun P Marlatt

Aleksey Lipchin

Alexander Chau

Levi Glozman

Richard Butt

Sreemanananth Sadanand

Mitul Saha

Peter Anderholm

Chia Ying Lee

Scott Michael Alazraki

Yin Wang

James C Duran

Roger David Donaldson

Deborah A Gruenhagen

Barbara R Doutre

Nicholas John Alcock

Steven Gilmore

Dharanish Kedarisetti

Ken Jessen

Qifan Liang

Kangyan Liu

Matthew Seeley

Aravind Anantha

Weijuan Wu

Seyedmostafa Azizabadifarahani

Doris E Ford

Hao Zhang

Dung-Han Lee

An event detected in video is encoded as a binary vector. A set of binary vectors representative of the video may be so generated and stored in a queryable datastore. A query is encoded as a binary vector representative of a queried event. The query binary vector is compared to the set of binary vectors generated for the video and a result indicative of a similarity of the query binary vector to the set of binary vectors is returned.

Searchable video with binary vectors

A hybrid operation of a license plate recognition (LPR) system and infrastructure monitoring is provided. The system takes advantage of a first mode of operation of the LPR system, by running an infrastructure analytical tool which gathers infrastructure images in parallel with license plate detection. Analytics are applied, via a cloud based analytics engine, to provide detection of infrastructure anomalies, and prediction of potential infrastructure incidents. The system further generates a trigger alert warning of a potential infrastructure incident and recommendation to address the potential infrastructure incident.

Hybrid operation of license plate recognition (LPR) camera for infrastructure monitoring

Alias capture to support searching for an object-of-interest is disclosed. A method includes capturing, using a camera with a defined field of view, video image frames that include a moving object-of-interest. The method also includes tracking the object-of-interest over a period of time starting when the object-of-interest enters the field of view and ending when the object-of-interest exits the field of view. The method also includes detecting, at a point in time in-between the start and end of the period of time of the tracking, a threshold exceeding change in an appearance of the object-of-interest. The method also includes creating, before the end of the period of time of the tracking, a new object profile for the object-of-interest in response to the detecting of the threshold exceeding change.

Alias capture to support searching for an object-of-interest

Systems, devices, and technical methods of the present disclosure leverage digital visitor logs from confinement facilities to identify people of interest that may be involved in incidents to which first responders are dispatched. When a phone call is received at phone public safety access point, a first query including a name associated with the call is transmitted to a digital visitor log for a confinement facility. A digital response to the first query identifies a visitee who was visited by a visitor by that name while the visitee was in confinement. The visitee's name is then transmitted in a second query to a digital repository containing release records; a digital response indicates the visitee was released before the call was received. An electronic notification that identifies the visitee is transmitted to a device associated with an agent who is responding to the call.

Systems to infer identities of persons of interest rapidly and alert first responders

A method, system and computer program product for emulating depth data of a three-dimensional camera device is disclosed. The method includes concurrently operating the radar device and the 3D camera device to generate training radar data and training depth data respectively. Each of the radar device and the 3D camera device has a respective field of view. The field of view of the radar device overlaps the field of view of the 3D camera device. The method also includes inputting the training radar and depth data to the neural network. The method also includes employing the training radar and depth data to train the neural network. Once trained, the neural network is configured to receive real radar data as input and to output substitute depth data.

Method, system and computer program product for emulating depth data of a three-dimensional camera device

Methods, systems, and techniques for tagless tracking of an object-of-interest are disclosed. Image and non-image data are generated across a plurality of camera-specific regions, and the object-of-interest is tracked over a global map formed as a composite of these regions.

Method and system for tracking an object-of-interest without any required tracking tag theron

Methods, systems, and techniques for monitoring an object-of-interest within a region involve receiving at least data from two sources monitoring a region and correlating that data to determine that an object-of-interest depicted or represented in data from one of the sources is the same object-of-interest depicted or represented in data from the other source. Metadata identifying that the object-of-interest from the two sources is the same object-of-interest is then stored for later use in, for example, object tracking.

Sensor fusion for monitoring an object-of-interest in a region

Methods for detecting anomalies in a geographic area include receiving, from an electronic computing device, expected relationship data indicating expected relationships between a plurality of entities within the geographic area; detecting the plurality of entities within the geographic area; generating observed relationship data indicating observed relationships between the plurality of entities; identifying the expected relationships between the plurality of entities based on the expected relationship data; determining that a given observed relationship between two entities of the plurality of entities is likely to represent an anomaly based on the expected relationship data; and providing an electronic notification to a safety officer, the electronic notification indicating that the given observed relationship is likely to represent the anomaly.

Systems and methods for detecting anomalies in geographic areas

There is provided an appearance search system comprising one or more cameras configured to capture video of a scene, the video having images of objects. The system comprises one or more processors and memory comprising computer program code stored on the memory and configured when executed by the one or more processors to cause the one or more processors to perform a method. The method comprises identifying one or more of the objects within the images of the objects. The method further comprises implementing a learning machine configured to generate signatures of the identified objects and generate a signature of an object of interest. The system further comprises a network configured to send the images of the objects from the camera to the one or more processors. The method further comprises comparing the signatures of the identified objects with the signature of the object of interest to generate similarity scores for the identified objects, and transmitting an instruction for presenting on a display one or more of the images of the objects based on the similarity scores.

System and method for appearance search

A computer-implemented method comprises detecting, with a presence detector such as a radar device, a presence of a person at a location such as an ATM vestibule. In response thereto, a timer is initiated. After initiating the timer, a portal sensor is used to detect a change in a status of a portal permitting access to the location. In response thereto, the timer is adjusted (for example the timer is reset). Thus, multiple consecutive normal usages of the vestibule do not unnecessarily trigger an alarm.

Presence detection and uses thereof

Methods, systems, and techniques for facilitating improved training of a supervised machine learning process, such as a decision tree. First and second object detections of an object depicted in a video are respectively generated using first and second object detectors, with the second object detector requiring more computational resources than the first object detector to detect the object. Whether a similarity and a difference between the first and second object detections respectively satisfy a similarity threshold and a difference threshold is determined. When the similarity threshold is satisfied, the first object detection is stored as a positive example for the machine learning training. When the difference threshold is satisfied, the first object detection is stored as a negative example for the machine learning training.

Method and system for facilitating improved training of a supervised machine learning process

There are described methods and systems for facilitating identification of an object-of-interest. A face similarity score and a body similarity score of a query image relative to a gallery image are determined. A fused similarity score of the query image relative to the gallery image is determined by applying a relationship between the face similarity score, the body similarity score, and the fused similarity score. The fused similarity score is indicative of whether or not the object-of-interest and the potential object-of-interest are the same object-of-interest. For example, a machine learning process is used to fuse the face similarity score and the body similarity into the fused similarity score. The process is repeated for multiple gallery images. The gallery images may then be ranked according to their respective fused similarity scores.

Method and system for facilitating identification of an object-of-interest

A process for adjusting an amount of video analytics data reported by video capturing devices deployed in a given location. In operation, an electronic computing device detects occurrence of an incident at an incident location based on processing video data or sensor data that are captured corresponding to the incident location. When it is determined that a video capturing device that is deployed within a predetermined distance from the incident location is currently configured with a second video analytics data reporting threshold that is greater than the first video analytics data reporting threshold, the electronic computing device transmits an instruction to the video capturing device to lower the second video analytics data reporting threshold to the first video analytics data reporting threshold and further report video analytics data corresponding to a video stream captured by the video capturing device as a function of the first video analytics data reporting threshold.

Growing community of inventors

Woburn, MA, United States of America

Yanyan Hu