An example method includes causing a light projecting system of a distance sensor to project a three-dimensional pattern of light onto an object, wherein the three-dimensional pattern of light comprises a plurality of points of light that collectively forms the pattern, causing a light receiving system of the distance sensor to acquire an image of the three-dimensional pattern of light projected onto the object, causing the light receiving system to acquire a two-dimensional image of the object, detecting a feature point in the two-dimensional image of the object, identifying an interpolation area for the feature point, and computing three-dimensional coordinates for the feature point by interpolating using three-dimensional coordinates of two points of the plurality of points that are within the interpolation area.

An apparatus projecting light onto a projection surface comprises: a substrate having disposed thereon two or more LED clusters and two or more micro-lenses, each LED cluster comprising a plurality of LEDs and each of the micro-lenses being disposed the plurality of LEDs. Each of the LED clusters is arranged to emit light through each of the micro-lenses in a pattern of dots. A center of at least one LED cluster is off-set from an optical center of the micro-lens of its LED cluster. A projected image includes arrangements of individual dots and/or areas of smooth light resulting from the pattern of dots.

There is provided a lighting device arranged to produce a controllable light beam for illuminating a scene. The device comprises an addressable spatial light modulator arranged to provide a selectable phase delay distribution to a beam of incident light. The device further comprises Fourier optics arranged to receive phase-modulated light from the spatial light modulator and form a light distribution. The device further comprises projection optics arranged to project the light distribution to form a pattern of illumination as said controllable light beam.

A method for detecting the presence of foreign fluids on surface comprises estimating an expected polarization response for a foreign fluid desired to be detected. Oil from an oil spill is one such foreign fluid. A polarimeter records raw image data of a surface (e.g., the surface of water) to obtain polarized images of the surface. IR and polarization data products are computed from the polarized images. The IR and polarization data products are converted to multi-dimensional data set to form multi-dimensional imagery. Contrast algorithms are applied to the multi-dimensional imagery to form enhanced contrast images, from which foreign fluids can be automatically detected.

An information processing apparatus including one or more processors that calculate a degree of polarization on the basis of polarization information in each of multiple directions, which is detected from a target region including a region through which polarized light passes, and extract a region in which an object is present on the basis of the degree of polarization.

A system for capturing a 3D image of a subject includes a detection device which is structured to capture images of the subject and surrounding environment, a projection device which is structured to provide a source of structured light, and a processing unit in communication with the detection device and the projection device. The processing unit is programmed to: analyze an image of the subject captured by the detection device; modify one or more of: the output of the projection device or the intensity of a source of environmental lighting illuminating the subject based on the analysis of the image; and capture a 3D image of the subject with the detection device and the projection device using the modified one or more of the output of the projection device or the intensity of the source of environmental lighting illuminating the subject.

An infrared projector, an imaging device, and a terminal device are provided. The infrared projector provided herein includes an infrared source, a light reflective section, a light filtering section, and at least one driving component. The infrared source is configured to emit infrared light. The light reflective section is configured to receive and reflect the infrared light from the infrared source. The light filtering section is configured to receive the infrared light reflected by the light reflective section. The at least one driving component is configured to drive at least one of the light reflective section and the light filtering section to move.

A device for monitoring occupants of seats in a passenger compartment of a vehicle comprises a heat sink divided into a plurality of sections. Each of the sections comprises a base and cooling fins. The bases extend along a common axis and define a central niche therebetween. Structured light sources are attached to the sections. The structured light sources have an optical element for forming a structured light pattern. The structured light sources are oriented along the common axis and at oblique angles to the central niche, such that the structured light patterns, in combination, are directed such that they would cover occupants of seats of the vehicle. A camera is attached to the niche and configured to capture image patterns resulting from distortion of the plurality of structured light patterns by the occupants of the seats.

A monitoring system includes a memory, and a processor coupled to the memory and configured to detect a face area of a subject from a captured image divided into a plurality of blocks according to a number of light emitting elements that irradiate an image capturing range, and control a light emission intensity of a light emitting element corresponding to a block including the face area among the plurality of blocks according to one of a position of the face area and a size of the face area.

The method for item recognition can include: optionally calibrating a sampling system, determining visual data using the sampling system, determining a point cloud, determining region masks based on the point cloud, generating a surface reconstruction for each item, generating image segments for each item based on the surface reconstruction, and determining a class identifier for each item using the respective image segments.