A measurement device includes: an optical system that splits incident light into two lights to emit one light as measurement light to a measurement object and the other light as reference light to a reference surface, and recombines the two lights to emit combined light; a light emitter that emits light entering the optical system; an imaging system that takes an image of output light emitted from the optical system; and a processor that executes measurement with regard to a predetermined measurement area of the measurement object, based on an interference fringe image taken by the imaging system, wherein the processor: obtains complex amplitude data at a predetermined position in an optical axis direction at predetermined intervals in at least a predetermined range in the optical axis direction, with regard to a specific area set in advance in the measurement area based on the interference fringe image.

A projection device can include: an illuminating unit for emitting light; and a projection unit having a mirror surface, the projection unit being designed to project the light emitted by the illuminating device by means of the mirror surface into an object space and to shape it into different spatially structured light patterns in the object space. The projection device is distinguished in that the mirror surface is deformable, at least in regions, and in that the projection unit, for forming the different spatially structured light patterns in the object space, has at least one actuator for deforming the mirror surface, at least in regions. The present subject matter furthermore relates to a projection method, to a device, and to a method for detecting a three-dimensional contour.

A method for semi-dense depth estimation includes receiving, at an electronic device, a control signal of a speckle pattern projector (SPP and receiving from each sensor of a dynamic vision sensor (DVS) stereo pair, an event stream of pixel intensity change data, wherein the event stream is time-synchronized with the control signal of the SPP. The method further includes performing projected light filtering on the event stream of pixel intensity change data for each sensor of the DVS stereo pair, to generate synthesized event image data, the synthesized event image data having one or more channels, each channel based on an isolated portion of the event stream of pixel intensity change data and performing stereo matching on at least one channel of the synthesized event image data for each sensor of the DVS stereo pair to generate a depth map for at least a portion of the field of view.

In one embodiment, a method for calculating a distance to an object includes projecting a plurality of beams simultaneously from a light source, wherein the plurality of beams causes a plurality of lines of dots to be projected onto the object, and wherein the plurality of lines of dots are orientated parallel to each other, capturing an image of a field of view, wherein the object is visible in the image and the plurality of lines of dots is also visible in the image, and calculating the distance to the object using information in the image.

A method includes projecting a first reference image onto a first surface region that includes a component target; capturing a first pair of images that both include (i) the first reference image, (ii) a first ring target located at a first position on an inner ring, (iii) a third ring target located at a third position on an outer ring, and (iv) the component target; projecting a second reference image onto a second surface region; capturing a second pair of images that both include (i) the second reference image, (ii) a second ring target located at a second position on the inner ring, and (iii) a fourth ring target located at a fourth position on the outer ring; and based on the first pair of images and the second pair of images, generating coordinate data that defines the first surface region and the second surface region within a coordinate space.

A three-dimensional sensor system includes three cameras, a projector, and a processor. The projector simultaneously projects at least two linear patterns on the surface of an object. The three cameras synchronously capture a first two-dimensional (2D) image, a second 2D image, and a third 2D image of the object, respectively. The processor extracts a first set and a second set of 2D lines from the at least two linear patterns on the first 2D image and the second 2D image, respectively; generates a candidate set of three-dimensional (3D) points from the first set and the second set of 2D lines; and selects, from the candidate set of 3D points, an authentic set of 3D points that matches a projection contour line of the object surface by: performing data verification on the candidate set of 3D points using the third 2D image, and filtering the candidate set of 3D points.

A head-mounted device (HMD) is configured to perform depth detection in conjunction with movement tracking. The HMD includes a stereo camera pair comprising a first camera and a second camera, both of which are mounted on the HMD. The fields of view for both of the cameras overlap to form an overlapping field of view. These cameras are configured to detect both visible light and infrared (IR) light. The HMD also includes an IR dot-pattern illuminator that is configured to emit an IR dot-pattern illumination. The HMD uses the IR dot-pattern illumination to determine an object's depth. The HMD also includes one or more flood IR light illuminators that emit a flood of IR light. The HMD uses the flood of IR light to track at least its own movements, and sometimes even hand movements, in various environments, even low light environments.

A head-mounted device (HMD) is configured to perform depth detection in conjunction with movement tracking. The HMD includes a stereo camera pair comprising a first camera and a second camera, both of which are mounted on the HMD. The fields of view for both of the cameras overlap to form an overlapping field of view. These cameras are configured to detect both visible light and infrared (IR) light. The HMD also includes an IR dot-pattern illuminator that is configured to emit an IR dot-pattern illumination. The HMD uses the IR dot-pattern illumination to determine an object's depth. The HMD also includes one or more flood IR light illuminators that emit a flood of IR light. The HMD uses the flood of IR light to track at least its own movements, and sometimes even hand movements, in various environments, even low light environments.

A method and system for scanning an outer surface of a three-dimensional object, the outer surface being reflective, the method comprising the following steps: (a) projecting a light pattern on the object with a relative movement between the light pattern and the object; (b) recording with cameras images of the light pattern reflected by the outer surface during the relative movement; (c) processing the recorded reflection images by identifying the outline of the light pattern and determining from the outline characteristics of the outer surface; wherein the light pattern comprises at least one homogenously illuminated strip extending transversally to a direction of the relative movement with at least one border with a non-straight profile so as to form a non-constant width of the strip; and in step (c) the speed of the relative movement is taken into account for determining a three-dimensional definition of the outer surface.

Methods and systems for depth sensing are provided. A system includes a first and second optical sensor each including a first plurality of photodetectors configured to capture visible light interspersed with a second plurality of photodetectors configured to capture infrared light within a particular infrared band. The system also includes a computing device configured to (i) identify first corresponding features of the environment between a first visible light image captured by the first optical sensor and a second visible light image captured by the second optical sensor; (ii) identify second corresponding features of the environment between a first infrared light image captured by the first optical sensor and a second infrared light image captured by the second optical sensor; and (iii) determine a depth estimate for at least one surface in the environment based on the first corresponding features and the second corresponding features.