Abstract: A computer-vision system or engine that (a) generates from a pixel stream a digital representation of a person and (b) determines attributes or characteristics of the person from that digital representation and (c) based on those attributes or characteristics, outputs data to a cloud-based analytics system that enables that analytics system to identify and also to authenticate the person. The attributes or characteristics of the person include their pose, and the system or engine analyses that pose to extract a facial image from a video stream that is the best facial image for use by the cloud-based analytics system to identify and authenticate the person. The computer-vision system or engine outputs the facial image to the cloud-based analytics system, but does not output the full-frame real-time video to the cloud-based analytics system.

Abstract: A computer-vision-based monitoring system for monitoring an occupant of a road vehicle, including: a server located external to the vehicle and forming part of a distributed computing infrastructure; a first camera in the vehicle to capture an image of the environment external to the vehicle; a second camera in the vehicle to capture an image of occupants in the vehicle; a computer vision sub-system connected to the cameras in the vehicle, having an edge layer of the infrastructure; a vehicle occupant analysis sub-system trained using machine learning, wherein the vehicle occupant analysis sub-system uses its training to analyse the pose of a person and to detect if the person's head is directed towards the second camera to indicate that the person is giving attention to the camera.

Abstract: The field of the invention relates to computer vision systems and methods providing real time data analytics on detected people or objects in the home environment or other environments. It is based on an embedded engine that analyses an image from a raw sensor and virtualised the image into a digital representation enabling a digital understanding of the environment while guarantying privacy. It comprises multiple image processing blocks and embedded firmware.

Abstract: A computer-vision-based monitoring system for a road vehicle, including: (i) a server located external to the road vehicle and forming part of a distributed computing infrastructure; (ii) a first camera positioned in, or configured to be attached to, the road vehicle and configured to capture an image of the environment external to the road vehicle; (iii) a computer vision sub-system connected to the first camera, in which the computer vision sub-system is configured to be locatable in the road vehicle, and forms or includes at least some of an edge layer of the distributed computing infrastructure; (iv) a person tracking sub-system that is connected to, or is part of, the computer vision sub-system, the person tracking sub-system having been trained using machine learning, wherein the person tracking sub-system is configured to use its training using the machine learning to analyse a trajectory of a person approaching the road vehicle.

Abstract: A computer vision-based monitoring system for counting the number of occupants in a road vehicle, including a server located external to the road vehicle and forming part of a distributed computing infrastructure; a first camera positioned in, or configured to be attached to, the road vehicle and configured to capture an image of the environment external to the road vehicle; a second camera positioned in, or configured to be attached to, the road vehicle and configured to capture an image of one or more occupants in the road vehicle; a computer vision sub-system connected to the cameras, configured to be locatable in the road vehicle, and includes an edge layer of the distributed computing infrastructure; a vehicle occupant counting sub-system trained using machine learning, wherein the sub-system is configured to use its training to count the number of occupants in the road vehicle.

Abstract: The field of the invention relates to computer vision systems and methods providing real time data analytics on detected people or objects in the home environment or other environments. It is based on an embedded engine that analyses an image from a raw sensor and virtualised the image into a digital representation enabling a digital understanding of the environment while guarantying privacy. It comprises multiple image processing blocks and embedded firmware.

Abstract: A computer-vision system or engine that (a) generates from a pixel stream a digital representation of a person and (b) determines attributes or characteristics of the person from that digital representation and (c) based on those attributes or characteristics, outputs data to a cloud-based analytics system that enables that analytics system to identify and also to authenticate the person. The attributes or characteristics of the person include their pose, and the system or engine analyses that pose to extract a facial image from a video stream that is the best facial image for use by the cloud-based analytics system to identify and authenticate the person. The computer-vision system or engine outputs the facial image to the cloud-based analytics system, but does not output the full-frame real-time video to the cloud-based analytics system.

Abstract: The field of the invention relates to computer vision systems and methods providing real time data analytics on detected people or objects in the home environment or other environments. It is based on an embedded engine that analyses an image from a raw sensor and virtualised the image into a digital representation enabling a digital understanding of the environment while guarantying privacy. It comprises multiple image processing blocks and embedded firmware.

Abstract: The field of the invention relates to computer vision systems and methods providing real time data analytics on detected people or objects in the home environment or other environments. It is based on an embedded engine that analyses an image from a raw sensor and virtualised the image into a digital representation enabling a digital understanding of the environment while guarantying privacy. It comprises multiple image processing blocks and embedded firmware.

Abstract: The field of the invention relates to computer vision systems and methods providing real time data analytics on detected people or objects in the home environment or other environments. It is based on an embedded engine that analyses an image from a raw sensor and virtualised the image into a digital representation enabling a digital understanding of the environment while guarantying privacy. It comprises multiple image processing blocks and embedded firmware.

Abstract: The field of the invention relates to computer vision systems and methods providing real time data analytics on detected people or objects in the home environment or other environments. It is based on an embedded engine that analyses an image from a raw sensor and virtualised the image into a digital representation enabling a digital understanding of the environment while guarantying privacy. It comprises multiple image processing blocks and embedded firmware.

Abstract: The field of the invention relates to computer vision systems and methods providing real time data analytics on detected people or objects in the home environment or other environments. It is based on an embedded engine that analyses an image from a raw sensor and virtualised the image into a digital representation enabling a digital understanding of the environment while guarantying privacy. It comprises multiple image processing blocks and embedded firmware.

Abstract: The field of the invention relates to computer vision systems and methods providing real time data analytics on detected people or objects in the home environment or other environments. It is based on an embedded engine that analyses an image from a raw sensor and virtualised the image into a digital representation enabling a digital understanding of the environment while guarantying privacy. It comprises multiple image processing blocks and embedded firmware.

Abstract: An image processing method is provided. The method includes acquiring a video. The method includes using an object detection engine to detect a person in the video. The object detection engine is integrated with an image signal processing pipeline. The method includes transmitting the video over a network. The method includes determining that the detected person has moved less than a pre-set distance. The method includes, responsive to the determining, pausing transmission of the video. An embedded image processor including an object detection engine is also provided.

Abstract: A computer-vision system or engine that (a) generates from a pixel stream a digital representation of a person and (b) determines attributes or characteristics of the person from that digital representation and (c) based on those attributes or characteristics, outputs data to a cloud-based analytics system that enables that analytics system to identify and also to authenticate the person. The attributes or characteristics of the person include their pose, and the system or engine analyses that pose to extract a facial image from a video stream that is the best facial image for use by the cloud-based analytics system to identify and authenticate the person. The computer-vision system or engine outputs the facial image to the cloud-based analytics system, but does not output the full-frame real-time video to the cloud-based analytics system.

Abstract: The field of the invention relates to computer vision systems and methods providing real time data analytics on detected people or objects in the home environment or other environments. It is based on an embedded engine that analyses an image from a raw sensor and virtualised the image into a digital representation enabling a digital understanding of the environment while guarantying privacy. It comprises multiple image processing blocks and embedded firmware.

Abstract: The field of the invention relates to computer vision systems and methods providing real time data analytics on detected people or objects in the home environment or other environments. It is based on an embedded engine that analyses an image from a raw sensor and virtualised the image into a digital representation enabling a digital understanding of the environment while guarantying privacy. It comprises multiple image processing blocks and embedded firmware.

Abstract: A method of forming a control parameter dependent on ambient light. The method comprises the steps of acquiring light values from an ambient light sensor and acquiring positional status values from a positional status sensor. The control parameter depends on the light values and is filtered in dependence on the positional status values.

Abstract: In a method of enhancing the appearance of a digital image on an electronic display, Ambient Light Sensor (ALS) and Screen Brightness (SB) inputs are combined with a calibration input 12 to generate a first strength parameter 22, including an alpha component that is dependent only upon the properties of the display. Then a further, content-based input 24 is also combined to generate a second strength parameter 26, including a beta component that is dependent only upon a content type, or a content quality, or both.

Abstract: There is provided a method for estimating a distance of an object detected by an image sensor. Multiple detections are performed automatically to detect features of an object and to estimate the object proportions, which are then used to relate to additional measurements such as the distance of the object from the image sensor. The method detects human and non-human objects. The method uses available anthropometry tables. The method takes into account the image sensor optical aberrations such as lens distortion. A related system and a related computer program product are also provided.