A slit lamp microscope of an aspect example includes a scanner and a data processor. The scanner is configured to scan an anterior segment of a subject's eye with slit light to collect a plurality of cross sectional images. The data processor is configured to generate opacity distribution information that represents a distribution of an opaque area in a crystalline lens, based on the plurality of cross sectional images collected by the scanner.

Techniques for aligning images generated by an integrated camera physically mounted to an HMD with images generated by a detached camera physically unmounted from the HMD are disclosed. A 3D feature map is generated and shared with the detached camera. Both the integrated camera and the detached camera use the 3D feature map to relocalize themselves and to determine their respective 6 DOF poses. The HMD receives the detached camera's image of the environment and the 6 DOF pose of the detached camera. A depth map of the environment is accessed. An overlaid image is generated by reprojecting a perspective of the detached camera's image to align with a perspective of the integrated camera and by overlaying the reprojected detached camera's image onto the integrated camera's image.

A stereoscopic image generating method is provided. The method includes: processing a first image to obtain depth data of each pixel in the first image, and generating a first depth-information map, wherein the first depth-information map includes depth information corresponding to each pixel; performing uniform processing on a plurality of edge pixels which are within a predetermined width from a plurality of edges of the first depth-information map, so that the processed edge pixels have the same depth information to establish a second depth-information map; setting a pixel offset corresponding to each pixel in the first image based on the depth information corresponding to each pixel of the second depth-information map; performing pixel offset processing on the first image to generate a second image; and outputting the first image and the second image to the display unit to display a stereoscopic image.

The present invention relates to a method for detecting changes in the ore grade of a rock face in near real time. The method includes the step of providing a scanning system having at least a hyperspectral imager, a position system, a LiDAR or range determination unit and computational resources. Further, the method involves determining a precise location of the scanning system utilising the position system. The rock face is scanned with the range determination unit to determine rock face position information. The method involves scanning the rock face with the hyperspectral imager to produce a corresponding rock face hyperspectral image. Further the method involves utilising the computational resources to fuse together the rock face position information and the corresponding rock face hyperspectral image to produce a rock face position and content information map of the rock face.

Disclosed herein are methods, devices, modules, and systems which may be employed to accurately track, and subsequently target, objects of interest relative to a moving body, such as a vehicle. An object tracking method may be implemented by a detection system with a sensor coupled to the moving body. A targeting system may be used to target objects tracked by the detection system, such as for automated crop cultivation or maintenance. Devices disclosed herein may be configured to locate, identify, and autonomously target a weed with a beam, such as a laser beam, which may burn or irradiate the weed. The methods, devices, modules, and systems may be used for agricultural crop management or for at-home weed control.

Provided are methods for localization functional safety, which can include systems, methods, and computer program products are also provided. In examples, a method includes applying a transform to a source point cloud and calculating a second metric based on the application of the transform to the source point cloud and a map at a higher ASIL level. A first metric is determined based on a localization function that executes at a lower ASIL level. A deviation between a first metric and the second metric, is determined wherein the vehicle localization is validated when the deviation is less than a predetermined threshold.

A long-baseline and long depth-range stereo vision system is provided that is suitable for use in non-rigid assemblies where relative motion between two or more cameras of the system does not degrade estimates of a depth map. The stereo vision system may include a processor that tracks camera parameters as a function of time to rectify images from the cameras even during fast and slow perturbations to camera positions. Factory calibration of the system is not needed, and manual calibration during regular operation is not needed, thus simplifying manufacturing of the system.

The subject disclosure relates to techniques for selecting points of an image for processing with LiDAR data. A process of the disclosed technology can include steps for receiving an image comprising a first image object and a second image object, processing the image to place a bounding box around the first image object and the second image object, and processing an image area within the bounding box to identify a first image mask corresponding with a first pixel region of the first image object and a second image mask corresponding with a second pixel region of the second image object. Systems and machine-readable media are also provided.

A CPU acquires a distance image or a visible light image obtained by imaging a marker for measuring an SID as an object to be imaged using a TOF camera or a visible light camera. In addition, the CPU derives a marker distance between the TOF camera or the visible light camera and the marker from an image of a marker region corresponding to the marker in the acquired distance image or visible light image. Further, the CPU derives the SID on the basis of the derived marker distance and information indicating a positional relationship between an acquisition unit and the marker.

A CPU acquires a distance image or a visible light image captured by a TOF camera or a visible light camera that has, as an imageable region, a region including an irradiation region which is a space in which a breast of a subject imaged by a mammography apparatus is irradiated with radiation emitted from a radiation source and detects whether or not a foreign object other than an object to be imaged is present in the irradiation region on the basis of the distance image or the visible light image.