An imaging device including a first filter that passes a first light and a second light; a second filter that blocks the second light; photoelectric converters that have sensitivity to the first light and the second light; and a processor, in which one of the photoelectric converters detects a light passing through the first filter to generate a first signal, one of the photoelectric converters detects a light passing through the first filter and the second filter to generate a second signal, and the processor performs the second light sensing based on the first signal and the second signal.

The present invention relates to a method for biometric authentication of a user of an electronic device comprising an optical fingerprint sensor 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 transparent display panel, the method comprises the steps of: illuminating the object with light of at least one distinguishable color; capturing at least two images of the object with an image sensor comprising a photodetector pixel array while illuminating the object with the light of at least one distinguishable color, wherein the images are captured for different applied forces by the object on the transparent display panel; and performing biometric authentication at least partly based on at least one relationship between the at least two images, the at least one relationship being related to a difference in pixel intensity from pixels in the photodetector pixel array arranged to detect light of the distinguishable color.

The present invention relates to a method for biometric authentication of a user of an electronic device comprising an optical fingerprint sensor 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 transparent display panel, the method comprises the steps of: illuminating the object with light of at least one distinguishable color; capturing at least two images of the object with an image sensor comprising a photodetector pixel array while illuminating the object with the light of at least one distinguishable color, wherein the images are captured for different applied forces by the object on the transparent display panel; and performing biometric authentication at least partly based on at least one relationship between the at least two images, the at least one relationship being related to a difference in pixel intensity from pixels in the photodetector pixel array arranged to detect light of the distinguishable color.

Systems and methods are provided for vehicle navigation. In one implementation, a navigation system for a host vehicle may comprise at least one processor. The processor may be programmed to receive from a first camera at least a first captured image representative of an environment of the host vehicle. The processor may be programmed to receive from a second camera at least a second captured image representative of the environment of the host vehicle. Both the first captured image and the second image includes a representation of the traffic light, and wherein the second camera is configured to operate in a primary mode where at least one operational parameter of the second camera is tuned to detect at least one feature of the traffic light. The processor may be further programmed cause at least one navigational action by the vehicle based on analysis of the representation of the traffic light.

Systems and methods are provided for vehicle navigation. In one implementation, a navigation system for a host vehicle may comprise at least one processor. The processor may be programmed to receive from a first camera at least a first captured image representative of an environment of the host vehicle. The processor may be programmed to receive from a second camera at least a second captured image representative of the environment of the host vehicle. Both the first captured image and the second image includes a representation of the traffic light, and wherein the second camera is configured to operate in a primary mode where at least one operational parameter of the second camera is tuned to detect at least one feature of the traffic light. The processor may be further programmed cause at least one navigational action by the vehicle based on analysis of the representation of the traffic light.

An imaging device includes an image sensing device and an image signal processor. The imaging sensing device includes a pixel array of sensing pixels comprising a first pixel for sensing incident light and having a first dynamic range and a second pixel for sensing incident light and having a second dynamic range, the pixel array of sensing pixels structured to have a ratio of a number of the first pixels to all sensing pixels to be higher than a ratio of a number of second pixels to all sensing pixels. The image signal processor is configured to receive and process pixel data from the image sensing device to generate a high dynamic range (HDR) image corresponding to a larger dynamic range than the first dynamic range or the second dynamic range, based on pixel data of the first pixels and pixel data of the second pixels in the pixel array.

An imaging device includes an image sensing device and an image signal processor. The imaging sensing device includes a pixel array of sensing pixels comprising a first pixel for sensing incident light and having a first dynamic range and a second pixel for sensing incident light and having a second dynamic range, the pixel array of sensing pixels structured to have a ratio of a number of the first pixels to all sensing pixels to be higher than a ratio of a number of second pixels to all sensing pixels. The image signal processor is configured to receive and process pixel data from the image sensing device to generate a high dynamic range (HDR) image corresponding to a larger dynamic range than the first dynamic range or the second dynamic range, based on pixel data of the first pixels and pixel data of the second pixels in the pixel array.

Methods and systems for using multiple hyperspectral cameras sensitive to different wavelengths to predict characteristics of objects for further processing, including recycling, are described. The multiple hyperspectral images can be used to predict higher resolution spectra by using a trained machine learning model. The higher resolution spectra may be more easily analyzed to sort plastics into a recyclability category. The hyperspectral images may also be used to identify and analyze dark or black plastics, which are challenging for SWIR, MWIR, and other wavelengths. The machine learning model may also predict the base polymers and contaminants of plastic objects for recycling. The hyperspectral images may be used to predict recyclability and other characteristics using a trained machine learning model.

Technology described herein includes a method that includes obtaining a set of color-coded sequences, each of which includes a sequence of colors. Each color-coded sequence has auto-correlation properties characterized by a merit factor larger than a first predetermined threshold, and cross-correlation properties among the color-coded sequences characterized by a demerit factor lower than a second predetermined threshold. A color-coded sequence is randomly selected from the set of color-coded sequences. A subject is illuminated in accordance with the sequence of colors in the selected color-coded sequence. A sequence of images of the subject are captured, and are temporally synchronized with illumination by the color-coded sequence. A filtered response image is generated from the sequence of images by a matched filtering process. Based on the filtered response image, it is determined that the subject is an alternative representation of a live person. In response, access to a secure system is prevented.

A method of human pose estimation, including, receiving an image frame, extracting in at least a first stage a first stage image feature based on the image frame, extracting in at least a second stage a second stage image feature based on the first stage image feature, extracting in at least a subsequent stage a subsequent stage image feature based on the second stage image feature, up-sampling the subsequent stage image feature, up-sampling the second stage image feature, concatenating the first stage image feature, the up-sampled second stage image feature and the up-sampled subsequent stage image feature and outputting a feature map based on an output of the concatenation.