Higher-speed image recognition processing can be implemented. A light receiving device according to an embodiment includes: a plurality of first filters (130) each transmitting an edge component in a predetermined direction in an incident image; a plurality of second filters (150) each transmitting light of a predetermined wavelength band in incident light; and a plurality of photoelectric conversion elements (PD) each photoelectrically converting light transmitted through one of the plurality of convolution filters and one of the plurality of color filters.

A multi-focal optical device comprises an image output unit outputting optical information, a linear polarizer uni-directionally polarizing the optical information, a first light reflector including a first polarizer transmitting light only in a first direction and reflecting the light transmitted through the first polarizer, a second light reflector including a second polarizer transmitting light only in a second direction perpendicular to the first direction and reflecting the light transmitted through the second polarizer, a light splitter splitting the optical information transmitted through the linear polarizer into the first light reflector and the second light reflector and reflecting the optical information reflected by one of the first light reflector or the second light reflector to allow the reflected optical information to form one focus, and a controller configured to control the linear polarizer to vary a direction of polarization of the linear polarizer.

The present invention provides a time-of-flight (TOF) device. The TOF device includes an infrared light emitter and an infrared light receiver, the infrared light emitter emits an infrared light along a first direction (X-axis), a right angle prism disposed on a movable base, and the infrared light passes through the right angle prism. A first actuator and a second actuator are respectively disposed beside the movable base. By actuating the first actuator, the right angle prism is tilted toward a second direction (Y axis), and by actuating the second actuator, the right angle prism is tilted toward a third direction (Z axis), and the second direction and the third direction are both perpendicular to the first direction.

An all-optical Diffractive Deep Neural Network (D.sup.2NN) architecture learns to implement various functions or tasks after deep learning-based design of the passive diffractive or reflective substrate layers that work collectively to perform the desired function or task. This architecture was successfully confirmed experimentally by creating 3D-printed D.sup.2NNs that learned to implement handwritten classifications and lens function at the terahertz spectrum. This all-optical deep learning framework can perform, at the speed of light, various complex functions and tasks that computer-based neural networks can implement, and will find applications in all-optical image analysis, feature detection and object classification, also enabling new camera designs and optical components that can learn to perform unique tasks using D.sup.2NNs. In alternative embodiments, the all-optical D.sup.2NN is used as a front-end in conjunction with a trained, digital neural network back-end.

An imaging device and an authentication controller are provided. The imaging device includes a modulator that includes a first pattern and that modulates light intensity with the first pattern, an image sensor that converts a light beam transmitted through the modulator into imaging data and outputs the imaging data, an image processing unit that performs, to the imaging data, a reconstruction process in which an image of the subject is reconstructed based on the cross-correlation operation between the imaging data and the pattern data having a second pattern and acquires an image, and a distance measurement unit that repeats the reconstruction process to the imaging data while changing a focus distance and acquires a focus distance having a highest contrast in a measurement region as a distance. The authentication controller performs image authentication and distance authentication using image data and distance data acquired by the imaging device.

An imaging device and an authentication controller are provided. The imaging device includes a modulator that includes a first pattern and that modulates light intensity with the first pattern, an image sensor that converts a light beam transmitted through the modulator into imaging data and outputs the imaging data, an image processing unit that performs, to the imaging data, a reconstruction process in which an image of the subject is reconstructed based on the cross-correlation operation between the imaging data and the pattern data having a second pattern and acquires an image, and a distance measurement unit that repeats the reconstruction process to the imaging data while changing a focus distance and acquires a focus distance having a highest contrast in a measurement region as a distance. The authentication controller performs image authentication and distance authentication using image data and distance data acquired by the imaging device.

An untethered apparatus for performing inside-out device tracking based on visual-inertial simultaneous location and mapping (SLAM) includes a dynamic vision sensor (DVS) configured to output an asynchronous stream of sensor event data, an inertial measurement unit (IMU) sensor configured to collect IMU data associated with motion of the apparatus at a predetermined interval, a processor and a memory. The memory contains instructions, which when executed by the processor, cause the apparatus to accumulate DVS sensor output over a sliding time window, the sliding time window including the predetermined interval, apply a motion correction to the accumulated DVS sensor output, the motion correction based on the IMU data collected over the predetermined interval, generate an event-frame histogram of DVS sensor events based on the motion correction, and provide the event-frame histogram of the DVS sensor events and the IMU data to a visual inertial SLAM pipeline.

According to one embodiment, an electronic device includes one or more processors. The one or more processors obtain an image captured by a camera with a filter having a first area transmitting light of a first wavelength range and a second area transmitting light of a second wavelength range. The image includes a first color-component image based on the light of the first wavelength range and a second color-component image based on the light of the second wavelength range. The one or more processors notify a user of an effective area for calculation of depth information based on a bias of color information in the first color-component image and the second color-component image.

A system for making a holographic medium for use in generating light patterns for eye tracking includes a light source configured to provide light and a beam splitter configured to separate the light into a first portion of the light and a second portion of the light that is spatially separated from the first portion of the light. The system also includes a first set of optical elements configured to transmit the first portion of the light for providing a first wide-field beam onto an optically recordable medium and one or more diffractive optical elements configured to receive the second portion of the light and project a plurality of separate light patterns onto the optically recordable medium for forming the holographic medium.

A digital imaging system and method of image data processing are provided. The system includes a main lens configured to focus light from a field of view for a plurality of depths of field and project a plurality of intermediary images representing the depths of field. An image sensor assembly is in a spaced relationship with the main lens and includes a light sensors grouped into sensor sub-arrays. An intermediate microlens array is disposed between the main lens and the image sensor assembly and includes intermediate micro lenses adjacent to and abutting one another to focus the intermediary images onto one of the sensor sub-arrays from a different perspective than another adjacent micro lens. A control unit captures and stores image data associated with the intermediary images and creates a three-dimensional depth map. The control unit also calculates distance information of objects to detect a gesture or obstacle.