Abstract: A device, system, and method for controlling vehicle-related functionality is provided. A system comprises: a vehicle comprising: a vehicle display; a mobile device comprising: a mobile display, the vehicle and the mobile device communicatively coupled to each other; a transceiver; and a controller. The controller is configured to: determine, via the transceiver, whether the vehicle is a first vehicle or a subsequent vehicle to arrive at an incident scene. When the vehicle is the first vehicle to arrive at the incident scene, the controller selectively enables: a first application for presentation at the vehicle display; and a second application for presentation at the mobile display. When the vehicle is the subsequent vehicle to arrive at the incident scene, the controller selectively enables: a third application, different from the first application, for presentation at the vehicle display; and a fourth application for presentation at the mobile display.

Abstract: A device, system, and method for controlling a vehicle-related display into an exited occupant support mode is provided. A system comprises: a vehicle egress sensor; a first vehicle comprising: a vehicle display; a mobile device comprising: a mobile display, the first vehicle and the mobile device communicatively coupled to each other; and a controller. The controller is configured to: determine, via the vehicle egress sensor, that an occupant has exited the first vehicle, or a second vehicle proximal to the first vehicle; and in response, selectively enable an exited occupant support mode at one or more of the vehicle display and the mobile display.

Abstract: One aspect provides a method for object detection including detecting, using an electronic processor, a plurality of candidate objects in a video using a convolutional neural network detection process and a background subtraction detection process and identifying, using the electronic processor, a candidate object from the plurality of candidate objects. The candidate object detected by the background subtraction detection process in a location of the video with no candidate objects detected by the convolutional neural network detection process. The method also includes determining, using the electronic processor, a background subtraction confidence level of the candidate object and categorizing, using the electronic processor, the candidate object as a detected object in the video in response to the background subtraction confidence level satisfying a background subtraction confidence threshold.

Abstract: 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.

Abstract: A device, method and system for pruning video analytics parameters is provided. A device analyzes images from a camera installed at an installation location using a full initial machine learning model trained to detect objects in the images using video analytics parameters, the full initial machine learning model being independent of the installation location. The device gathers, for a period of time, statistics for: frequency of use of the video analytics parameters and/or error generation frequency in detecting the objects in the images. After the period of time, based on the statistics, the device determines that given video analytics parameters meets one or more pruning conditions; and, in response, prunes the given video analytics parameters such that the full initial machine learning model, initially provided for the camera, changes to an updated machine learning model for the camera.

Abstract: Systems and methods for controlling camera settings of a camera to improve detection of faces in an uncontrolled environment are described. A first image is received from the camera, where the first image is captured by the camera at a first set of camera settings. A face is detected in the first image. The camera is adjusted to a second set of camera settings based on the detected face, where the second set of camera settings different from the first set of camera settings. A second image is received from the camera, where the second image is captured by the camera at the second set of camera settings. The face is detected in the second image. A quality metric of the face in the second image is determined where the quality metric is indicative of an image quality of the face in the second image.

Abstract: A system and method for improving a video characteristic of a video stream is described. According to various implementations of the invention, a changed region between a later-in-time image frame and an earlier-in-time image frame and an unchanged region between such two image frames are determined. A new improvement to the video characteristic is determined and applied to the changed region of the later-in-time image frame. A prior improvement to the video characteristic that was determined for the earlier-in-time image frame is applied to the unchanged region of the later-in-time image frame.

Abstract: One aspect provides a method for object detection including detecting, using an electronic processor, a plurality of candidate objects in a video using a convolutional neural network detection process and a background subtraction detection process and identifying, using the electronic processor, a candidate object from the plurality of candidate objects. The candidate object detected by the background subtraction detection process in a location of the video with no candidate objects detected by the convolutional neural network detection process. The method also includes determining, using the electronic processor, a background subtraction confidence level of the candidate object and categorizing, using the electronic processor, the candidate object as a detected object in the video in response to the background subtraction confidence level satisfying a background subtraction confidence threshold.

Abstract: A device, method and system for installing video analytics parameters at a video analytics engine is provided. An example device determines that a classification of a first camera is one or more of similar to, and same as, a respective classification of at least one second camera. The example device retrieves, from a memory, video analytics parameters associated with the at least one second camera, the video analytics parameters stored at the memory in association with the respective classification. The example device causes installing of the video analytics parameters at a video analytics engine associated with the first camera.

Abstract: 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.

Abstract: A system and method for improving a video characteristic of a video stream is described. According to various implementations of the invention, a changed region between a later-in-time image frame and an earlier-in-time image frame and an unchanged region between such two image frames are determined. A new improvement to the video characteristic is determined and applied to the changed region of the later-in-time image frame. A prior improvement to the video characteristic that was determined for the earlier-in-time image frame is applied to the unchanged region of the later-in-time image frame.

Abstract: 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.

Abstract: A method and apparatus for controlling a passage barrier is provided herein. During operation the apparatus will determine a location of all persons authorized to enter through the barrier (e.g., a door). The apparatus will also determine the location of all persons not authorized for entry. Based on the location information, the passage barrier will remain open or closed. More particularly, based on the location information, a door, for example, may remain locked unless properly accessed by an authorized person. Additionally, based on the location information, the door may remain open for all to pass through.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Disclosed is a process for performance monitoring and feedback for facial recognition systems. A first image for image matching from a camera capture device at a first location is received for purposes of image matching. A highest match confidence score of the first image to a particular stored enrollment image is determined. One or more image or user characteristics associated with the first image or first user is identified. The identified image or user characteristics and highest match confidence score are added to a facial recognition monitoring and feedback model. Subsequently, a particular one of the stored image or user characteristics consistently associated with a below-threshold highest match confidence score is identified, and a notification is displayed or transmitted including an indication of an identified facial recognition low match pattern and identifying the particular one of the stored image characteristics or user characteristics.

Abstract: Systems and methods for controlling camera settings of a camera to improve detection of faces in an uncontrolled environment are described. A first image is received from the camera, where the first image is captured by the camera at a first set of camera settings. A face is detected in the first image. The camera is adjusted to a second set of camera settings based on the detected face, where the second set of camera settings different from the first set of camera settings. A second image is received from the camera, where the second image is captured by the camera at the second set of camera settings. The face is detected in the second image. A quality metric of the face in the second image is determined where the quality metric is indicative of an image quality of the face in the second image.