Motorola Solutions, Inc.

Avigilon Corporation

Vigilant Solutions LLC

Pietro Russo

Mahesh Saptharishi

Peter L Venetianer

Kevin Piette

Yanyan Hu

Bo Yang Yu

Moussa Doumbouya

Azamat Sarkytbayev

Sven Rebien

Trent J Miller

Patrick Douglas Koskan

Shervin Sabripour

Daniel R Bestor

Peter Anderholm

Joseph Rafferty

William Fincannon

Barry Gravante

Francesca Schuler

Steven D Tine

Aleksey Lipchin

John B Preston

Eric Johnson

Lin Lin

Bert Van Der Zaag

Mariya Bondareva

Barbara R Doutre

Dharanish Kedarisetti

Kaveh Malakuti

Ron Wilson

Zili Li

Hao Zeng

John K Klingert

Patrick Henson

Danny Kam

Rupa S Vasara

Caroline J Watson

Fanlan Jing

Phong Truong Hoai

Phong Quang Dinh

Chan Yi Siew

Doran Ingalls

Howard Hoffman

A mobile device receives: images acquired by a camera, that depict a road that includes two road markers; and indicators of a marker width, a camera distance from the road, and a camera height. The mobile device provides, at a display screen: an image acquired by the camera; and two virtual road markers at fixed positions on the display screen, the two markers based on the width, distance, and height. The mobile device receives respective indicators of the two markers in the image, that are pinned to the two markers at the display screen in further images received from the camera as the two markers move in the further images, as an orientation of the camera changes. When the respective indicators about align with the two virtual markers overlaid on the further images on the display screen at the fixed positions, the mobile device provides a notification.

Device, method and system for assisted aiming of roadside cameras

Examples provide an imaging system including an image sensor; and an electronic processor in communication with the image sensor. The electronic processor is configured to determine a set of imaging parameters, and, for each iteration included in an iteration set, update the set of imaging parameters by: receiving an image captured by the image sensor using the set of imaging parameters, performing object recognition on the image to detect an object of interest, determining an object recognition confidence score, determining a set of external factors based on the image and/or information from a second sensor, linking the set of imaging parameters and the set of external factors to the object recognition confidence score, and training a predictive model for updating the set of imaging parameters using the object recognition confidence score, the set of imaging parameters, and the set of external factors.

Imaging system with object recognition feedback

Examples provide a variable zoom imaging system including an image sensor, a set of illumination channels, and a current driver circuitry for driving the set of illumination channels. Each respective illumination channel includes a set of light sources and a lens, and is associated with a respective focus distance. An electronic processor is configured to focus the image sensor to an object of interest, determine a distance from the image sensor to the object of interest, determine an exposure period for the image sensor, select a subset of illumination channels to activate based at least on the distance from the image sensor to the object of interest, and capture a first image of the object of interest using the image sensor by sequentially activating and deactivating each selected illumination channel of the subset for first respective time frames within the exposure period.

Time-multiplexed illumination blending

Methods and systems for tamper reduction for camera systems. One example system includes a camera with a first field of view configured to operate in a low-power mode and an active mode, an energy wave sensor with a second field of view, and an electronic processor. The electronic processor is configured to monitor, via the energy wave sensor, for an object within the second field of view and determine an object type of the object. In response to determining that the object type is a vehicle, the electronic processor transitions the camera from the low-power mode to the active mode and captures, via the camera, an image of the vehicle. In response to determining that the object type is a person, the electronic processor performs a tamper-monitoring action when the person is within a first predetermined range of a plurality of predetermined ranges of the system.

Tamper reduction for quick deploy camera system

Access control system and method to distinguish between tailgate and piggyback. The method includes receiving, from a camera positioned at an access point, one or more images of a first person at the access point and determining based on credential information whether the first person is authorized to enter through the access point. In response to determining that the first person is authorized to enter through the access point, the method includes determining, based on a consent-to-follow gesture of the first person detected in the one or more images, a number of guests of the first person requested to enter through the access point. The method also includes determining, based on the one or more images, a number of persons entering through the access point and generating an alert indicating unauthorized entry when the number of persons is greater than the number of guests.

Access control system and method to distinguish between tailgate and piggyback

A device, system, and method for an electronic response to a potential carjacking is provided. A device receives: a location and vehicle ignition status of a vehicle; and sensor data generated by one or more sensors that are onboard the vehicle, the sensor data different from the location and the vehicle ignition status. The device determines whether the location of the vehicle is associated with a carjacking type of location, and whether a combination of the vehicle ignition status and the sensor data meet a carjacking threshold condition. When both the location of the vehicle is associated with the carjacking type of location and the carjacking threshold condition is met, the device: outputs an alert at the vehicle indicative of, or associated with, the potential carjacking; and/or causes, a notification to be transmitted to a communication device associated with a public safety agency or a monitoring service.

Device, system, and method for an electronic response to a potential carjacking

One example device includes an electronic processor configured identify, based on an incident type and a role of an object associated with a public safety incident, an uncompleted task that is to be performed by a public safety officer and that is associated with the object associated with the public safety incident. The electronic processor may be configured to identify first data included in a captured data file associated with the public safety incident that was generated at least partially by monitoring the object. The electronic processor may be configured to determine a time period within the captured data file during which the first data is identified to be present, and display an indication of the uncompleted task and at least one of the time period within the captured data file, the first data, and a user-selectable link to allow a user to consume the first data.

Indicating that captured data is associated with an uncompleted task of an incident

Tendency detecting and analysis in support of generating one or more workflows via user interface interactions is disclosed. In accordance with the user interface interactions, processing user selection of one or more icons may generate at least one user-selectable option within a graphical user interface, where the user-selectable option corresponds to at least one workflow action. The workflow action may relate to an identified tendency of a person or a group of people.

Tendency detecting and analysis in support of generating one or more workflows via user interface interactions

Disclosed is a process for implementing an automated analytics for insuring compliance for a thermographic protocol for subjects seeking a temperature check, perhaps for entrance or access to a controlled space or facility. The automated video analytics utilize one or more cameras to detect thermography compliance violations based on whether the subject is perspiring, dehydrated, recently consumed a beverage, has exposed skin, excessive clothing, the amount and type of activity before getting screened, and/or the external and internal temperatures at the controlled facility associated with the subject. Furthermore, the automated video analytics may create a non-compliance score and/or control a timer for a non-compliance detection. Also, short and long term collected data may be analyzed for compliance to guidelines.

System and method for video analytics for thermography procedure compliance

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 and methods for dynamic radiometric thermal imaging compensation. The method includes analyzing a visible light image to determine an emissivity value for each of a plurality of visible light pixels making up the visible light image. The method includes associating each of the plurality of thermal pixels making up a thermal image corresponding to the visible light image with at least one of the plurality of visible light pixels making up the visible light image. The method includes generating a second thermal image by, for each of the plurality of thermal pixels making up the thermal image, determining a temperature value based on the thermal pixel value of the thermal pixel and the emissivity value of the at least one of the plurality of visible light pixels associated with the thermal pixel.

Dynamic radiometric thermal imaging compensation

Techniques for automatically detecting objects left behind. An example method includes receiving video frames of a scene from a three-dimensional (3D) camera and establishing, based on 3D depths associated with the video frames, a background of the scene. The method also includes detecting, in the frames, a foreground blob in the scene based on the foreground blob having a 3D depth that is different from the background. The method further includes detecting that the foreground blob has separated into a blob corresponding to a person and a second blob corresponding to an object, based on the person having a 3D depth that is different from the object. The method additionally includes determining that the person has been separated from the object for a threshold, and responsive to determining that the person has been separated from the object for the threshold, generating an alert indicating that the object is left behind.

Object left behind detection

A process of assigning video analytics tasks to computing devices. In operation, an electronic computing device obtains predicted scene data associated with a scene corresponding to which video data is to be captured at a particular time period using a video camera. The electronic computing device then estimates, based on the predicted scene data, an edge computing cost to be incurred to complete execution of a video analytics task at one or more edge computing devices and a cloud computing cost to be incurred to complete execution of the same video analytics task at one or more cloud computing devices. If the edge computing cost is lower than the cloud computing cost, then the electronic computing device assigns the video analytics task to the edge computing devices. Otherwise, then the electronic computing device assigns the video analytics task to the cloud computing devices.

Device and method for assigning video analytics tasks to computing devices

Automated processing, enforcement and intelligent management of vehicle operation violations is disclosed. A method, that is also disclosed, includes obtaining at least one image within which is shown at least a portion of a vehicle. The method also includes receiving image data for the at least one image, and analyzing the image data to generate a violation score for each of one or more potential vehicle operation violations for the vehicle. When the violation score is in-between an upper violation threshold and a lower consideration threshold, user input is obtained that either affirms or rejects existence of a violation and then, once the user input is obtained, a violation notification is generated only when the user input affirms the existence of the violation. When the violation score is higher than the violation threshold, the violation notification is generated without the user input being obtained.

Method, system and computer program product for automated processing, enforcement and intelligent management of vehicle operation violations

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

Growing community of inventors

Melrose, MA, United States of America

Pietro Russo