An apparatus (1, 5, 6) is described which includes two or more colour displays (2) arranged to provide piece-wise continuous illumination of a volume. The apparatus (1, 5, 6) also includes one or more cameras (3). Each camera (3) is arranged to image the volume. The apparatus (1, 5, 6) is configured to control the two or more colour displays (2) and the one or more cameras (3) to illuminate the volume with each of two or more illumination conditions. The apparatus (1, 5, 6) is also configured to obtain two or more sets of images. Each set of images is obtained during illumination of the volume with one or more corresponding illumination conditions. The two or more sets of images include sufficient information for calculation of a reflectance map and a photometric normal map of an object or subject (4) positioned within the volume. When viewed from the volume, the apparatus (1, 5, 6) only provides direct illumination of the volume from angles within a zone of a hemisphere. The zone is less than a hemisphere and corresponds to a first range (Δα) of latitudinal angles and a second range (Δβ) of longitudinal angles. Each of the first (Δα) and second ranges (Δβ) is no more than 17π/18.

A backlight face recognition method, a terminal device using the same, and a computer readable storage medium are provided. The method includes: performing a face detection on each original face image in an original face image sample set to obtain a face frame corresponding to the original face image; capturing the corresponding original face images from the original face image sample set, and obtaining a new face image containing background pixels corresponding to the captured original face images from the original face image sample set; preprocessing all the obtained new face images to obtain a backlight sample set and a normal lighting sample set; and training a convolutional neural network using the backlight sample set and the normal lighting sample set until the convolutional neural network reaches a preset stopping condition. The trained convolutional neural network will improve the accuracy of face recognition in complex background and strong light.

A backlight face recognition method, a terminal device using the same, and a computer readable storage medium are provided. The method includes: performing a face detection on each original face image in an original face image sample set to obtain a face frame corresponding to the original face image; capturing the corresponding original face images from the original face image sample set, and obtaining a new face image containing background pixels corresponding to the captured original face images from the original face image sample set; preprocessing all the obtained new face images to obtain a backlight sample set and a normal lighting sample set; and training a convolutional neural network using the backlight sample set and the normal lighting sample set until the convolutional neural network reaches a preset stopping condition. The trained convolutional neural network will improve the accuracy of face recognition in complex background and strong light.

A novel display apparatus is provided. The display apparatus includes a first layer including a plurality of pixel circuits, a second layer provided over the first layer, a plurality of optical lenses provided over the second layer, a display region, and a plurality of light-receiving regions. The display region includes a first pixel circuit provided in the first layer and a light-emitting device provided in the second layer. The light-receiving region includes a second pixel circuit provided in the first layer and a light-receiving device provided in the second layer. The plurality of light-receiving regions are provided around the display region. The optical lens is provided at a position overlapping with the light-receiving region.

A vehicle control system includes a camera configured to capture image data depicting a field of view proximate the vehicle is disclosed. The vehicle control system further includes a plurality of light sources in connection with the vehicle and a controller. The controller is configured to activate a plurality of lights in an alternating pattern and capture light reflected from at least one object with the camera at a time and corresponding to the alternating pattern of the plurality of lights. In response to variations in the light impinging upon the at least one object from the alternating pattern, the controller is configured to identify a distance of the object.

A vehicle control system includes a camera configured to capture image data depicting a field of view proximate the vehicle is disclosed. The vehicle control system further includes a plurality of light sources in connection with the vehicle and a controller. The controller is configured to activate a plurality of lights in an alternating pattern and capture light reflected from at least one object with the camera at a time and corresponding to the alternating pattern of the plurality of lights. In response to variations in the light impinging upon the at least one object from the alternating pattern, the controller is configured to identify a distance of the object.

A system can automatically adjust a virtual background used by a participant in a video conference to match lighting level conditions present in a foreground of a participant video stream captured at a participant device. The matching can be done by adjusting one or more virtual background parameters, including but not limited to, exposure, brightness, contrast, and ISO. In some implementations, the system can dynamically or automatically adjust the lighting levels of the virtual background based on changes that may occur to the lighting level of the foreground during the video conference.

A system can automatically adjust a virtual background used by a participant in a video conference to match lighting level conditions present in a foreground of a participant video stream captured at a participant device. The matching can be done by adjusting one or more virtual background parameters, including but not limited to, exposure, brightness, contrast, and ISO. In some implementations, the system can dynamically or automatically adjust the lighting levels of the virtual background based on changes that may occur to the lighting level of the foreground during the video conference.

An image processing apparatus which is capable of calculating appropriate irradiation conditions for invisible light so as to improve the image quality of a visible light image. The image processing apparatus includes a lighting unit. A feature value of the visible light image obtained by shooting of a subject irradiated with visible light provided by the lighting unit is calculated. A feature value of invisible light image obtained by shooting of the subject irradiated with invisible light provided by the lighting unit is calculated. Irradiation conditions for the invisible light to be provided by the lighting unit are calculated based on the feature value of the visible light image and the feature value of the invisible light image.

An image processing apparatus which is capable of calculating appropriate irradiation conditions for invisible light so as to improve the image quality of a visible light image. The image processing apparatus includes a lighting unit. A feature value of the visible light image obtained by shooting of a subject irradiated with visible light provided by the lighting unit is calculated. A feature value of invisible light image obtained by shooting of the subject irradiated with invisible light provided by the lighting unit is calculated. Irradiation conditions for the invisible light to be provided by the lighting unit are calculated based on the feature value of the visible light image and the feature value of the invisible light image.