Described herein is an object recognition system in low illumination conditions. A 3D InIm system can be trained in the low illumination levels to classify 3D objects obtained under low illumination conditions. Regions of interest obtained from 3D reconstructed images are obtained by de-noising the 3D reconstructed image using total-variation regularization using an augmented Lagrange approach followed by face detection. The regions of interest are then inputted into a trained CNN. The CNN can be trained using 3D InIm reconstructed under low illumination after TV-denoising. The elemental images were obtained under various low illumination conditions having different SNRs. The CNN can effectively recognize the 3D reconstructed faces after TV-denoising.

Provided is a system capable of determining a stress coping style of a test subject in a non-contact state. The system includes a biological information acquiring part which acquires biological information of a test subject in a non-contact state, and a determining part which determines a stress coping style of the test subject based on the biological information and a response pattern specified in advance. The response pattern is specified by a hemodynamic parameter.

A social engagement system includes a first exercise machine having a display able to present videos, a three-dimensional camera system, and local processing system able to provide pose estimation based on data from the three-dimensional camera system. The system also includes a communication module for connection to a cloud processing system, with the cloud processing system supporting connection to a second exercise machine having a display able to present videos, a three-dimensional camera system, and local processing system able to provide pose estimation based on data from the three-dimensional camera system. Additionally, the connection allows transfer of data useful for social engagement.

A thin lightweight imaging device is provided. A highly convenient imaging device is provided. The imaging unit includes an imaging unit, a memory, and an arithmetic circuit. The imaging unit includes a light-receiving device, a first light-emitting device, and a second light-emitting device. The first light-emitting device has a function of emitting light in a wavelength range that is different from a wavelength range of light emitted by the second light-emitting device. The imaging unit has a function of making the first light-emitting device emit light and acquiring first image data. The imaging unit has a function of making the second light-emitting device emit light and acquiring second image data. The memory has a function of retaining the first reference data and the second reference data. The arithmetic circuit has a function of correcting the first image data with the use of the first reference data retained in the memory and calculating first correction image data. The arithmetic circuit has a function of correcting the second image data with the use of the second reference data retained in the memory and calculating second correction image data. The arithmetic circuit has a function of combining the first correction image data and the second correction image data to generate synthesized image data. The light-receiving device includes a first pixel electrode, and the first light-emitting device includes a second pixel electrode on the same plane as the first pixel electrode.

An optical biometric imaging arrangement configured to be arranged under an at least partially transparent display panel, and configured to capture an image of an object located on an opposite side of the display panel, comprising: an image sensor comprising a photodetector pixel array; an array of light redirecting elements, each light redirecting element is configured to redirect light onto the pixel array, a color filter arranged between the array of light redirecting elements and the image sensor, the color filter comprising at least two color filter arrays of respective color filter elements being optically transmissive, a first color array comprising first color filter elements and a second color array comprising second color filter elements, the color filter arrays are arranged such that each photodetector pixel is at least partly covered by at least a first and a second color filter element.

A biometric capture device is operative to adjust one or more environmental parameters to enhance a range (e.g., distance) at which a biometric may be captured from a subject. For example, a sample biometric capture device may be, include, or otherwise incorporate a retinal or iris scanner configured to capture an image of the retina or iris (e.g., a biometric) when the retina or iris is illuminated by infrared light. Generally, the amount of infrared light required to accurately image the retina or iris increases with the distance of the subject's retina or iris from the image capture device. The biometric capture device may capture a facial image using a first image sensor, identify a face in the facial image, capture an iris image using a second image sensor guided by the facial image, and identify a person using the iris image.

In order to detect flying objects, a camera configuration is used for video monitoring of a monitoring space, and a control unit is used for controlling the camera configuration and evaluating the video frames recorded by the camera configuration. The camera configuration has an infrared illuminator for the monitoring space and at least one camera with an infrared image sensor. The infrared illuminator is preferably operated in a pulsed fashion synchronously with a measurement cycle of the camera.

A device to process an audio signal representing input sound includes a hand detector configured to generate a first indication responsive to detection of at least a portion of a hand over at least a portion of the device. The device also includes an automatic speech recognition system configured to be activated, responsive to the first indication, to process the audio signal.

A method of face anti-spoofing, comprising, receiving a near infra-red facial image, having a near infrared channel, receiving a red-green-blue facial image, having a red channel, a green channel and a blue channel, generating a synthetic three channel image based on the near infrared channel, the red channel, the green channel and the blue channel and training a deep neural network based on the synthetic three channel image.

A detection system that includes: an image capture apparatus configured to capture images of a scene located in the passenger compartment and a projection system configured to project structured light on the scene. The projection system has at least one projection device, each projection device being separate from the image capture apparatus so as to be mounted in the passenger compartment while being offset relative to the image capture apparatus. Each projection device is configured to project at least one structured light pattern. The detection system further includes an electronic control unit configured to analyze images captured using the image capture apparatus during the projection of one or several structured light pattern(s).