Abstract: One example temperature sensing device includes an electronic processor configured to receive a thermal image of a person captured by a thermal camera. The electronic processor is configured to determine a first temperature and a first location of a first hotspot on the person. The electronic processor is configured to determine a second location of a second hotspot on the person based on the second location being approximately symmetrical with respect to the first location about an axis, and the second hotspot having a second temperature that is approximately equal to the first temperature. The electronic processor is configured to determine a distance between the first location of the first hotspot and the second location of the second hotspot. In response to determining that the distance is within the predetermined range of distances, the electronic processor is configured to generate and output an estimated temperature of the person.

Abstract: Methods, systems, and techniques for enhancing use of two-dimensional (2D) video analytics by using depth data. Two-dimensional image data representing an image comprising a first object is obtained, as well as depth data of a portion of the image that includes the first object. The depth data indicates a depth of the first object. An initial 2D classification of the portion of the image is generated using the 2D image data without using the depth data. The initial 2D classification is stored as an approved 2D classification when the initial 2D classification is determined consistent with the depth data. Additionally or alternatively, a confidence level of the initial 2D classification may be adjusted depending on whether the initial 2D classification is determined to be consistent with the depth data, or the depth data may be used with the 2D image data for classification.

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: One example temperature sensing device includes an electronic processor configured to receive a thermal image of a person captured by a thermal camera. The electronic processor is configured to determine a first temperature and a first location of a first hotspot on the person. The electronic processor is configured to determine a second location of a second hotspot on the person based on the second location being approximately symmetrical with respect to the first location about an axis, and the second hotspot having a second temperature that is approximately equal to the first temperature. The electronic processor is configured to determine a distance between the first location of the first hotspot and the second location of the second hotspot. In response to determining that the distance is within the predetermined range of distances, the electronic processor is configured to generate and output an estimated temperature of the person.

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: A device, method and system for adjusting a configuration of a camera device is provided. An example device is in communication with an example camera device having a configuration. The device receives an image sequence from the camera device. The device processes the image sequence to determine a predicted location of a target object identified in the image sequence based on movement of the target object in the image sequence. The device adjusts the configuration of the camera device based on a stored configuration of the camera device, the stored configuration indicative of conditions at the predicted location.

Abstract: Systems for personalized intent prediction may perform a process including receiving image data depicting the behavior of a person on approach toward a secure location, generating intent data including data representing a current trajectory of the person on the current approach, comparing the intent data with a personal statistical model for the person that includes data representing trajectories associated with historical approaches by the person toward the secure location and respective result data indicating whether the historical approach resulted in the person entering the secure location, determining, dependent on the comparing, a personalized intent score representing a likelihood that the person intends to enter the secure location on the current approach, and pre-emptively enabling, or refraining from pre-emptively enabling, entry to the secure location prior to the person reaching the secure location based on whether the personalized intent score meets or exceeds a predetermined minimum confidence t

Abstract: Systems for personalized intent prediction may perform a process including receiving image data depicting the behavior of a person on approach toward a secure location, generating intent data including data representing a current trajectory of the person on the current approach, comparing the intent data with a personal statistical model for the person that includes data representing trajectories associated with historical approaches by the person toward the secure location and respective result data indicating whether the historical approach resulted in the person entering the secure location, determining, dependent on the comparing, a personalized intent score representing a likelihood that the person intends to enter the secure location on the current approach, and pre-emptively enabling, or refraining from pre-emptively enabling, entry to the secure location prior to the person reaching the secure location based on whether the personalized intent score meets or exceeds a predetermined minimum confidence t

Abstract: 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.

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: 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: 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: 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: 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: A cropped bounding box selection operation is performed on a video captured by a video capture and playback system, to select one or more cropped bounding boxes from the video for processing by a face detection operation. The cropped bounding box selection operation identifies objects from the video images and assigns a ranking to each identified object based on certain priority criteria; one or more cropped bounding boxes corresponding to the objects with the highest ranking(s) are then processed by the face detection operation to detect a face in each object.

Abstract: Methods, systems, and techniques for enhancing use of two-dimensional (2D) video analytics by using depth data. Two-dimensional image data representing an image comprising a first object is obtained, as well as depth data of a portion of the image that includes the first object. The depth data indicates a depth of the first object. An initial 2D classification of the portion of the image is generated using the 2D image data without using the depth data. The initial 2D classification is stored as an approved 2D classification when the initial 2D classification is determined consistent with the depth data. Additionally or alternatively, a confidence level of the initial 2D classification may be adjusted depending on whether the initial 2D classification is determined to be consistent with the depth data, or the depth data may be used with the 2D image data for classification.

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: 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.

Abstract: 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.