A method includes receiving, from a multiscopic image capture system, a plurality of images depicting a scene. The method includes determining, by application of a neural network based on the plurality of images, a disparity map of the scene. The neural network includes a plurality of layers, and the layers include a rectification layer. The method include determining a matching error of the disparity map based on differences between corresponding pixels of two or more images associated with the disparity map. The method includes back-propagating the matching error to the rectification layer of the neural network. Back-propagating the matching error includes updating one or more weights applied to the rectification layer.

A system to capture a plurality of two dimensional digital source images of scene by user, a smart device having a memory device for storing an instruction, a processor in communication with the memory and configured to execute the instruction, a plurality of digital image capture devices in communication with the processor and each image capture device configured to capture a digital image of the scene, the plurality of digital image capture devices positioned linearly in series within approximately an interpupillary distance, wherein a first digital image capture devices is centered proximate a first end of the interpupillary distance, a second digital image capture devices is centered on a second end of the interpupillary distance, and any remaining the plurality of digital image capture devices are evenly spaced therebetween, a display in communication with the processor, display configured to display multidimensional digital image sequence and add audio file thereto.

This disclosure relates to systems and methods for vehicle guidance. Stereo images may be obtained at different times using a stereo image sensor. A depth image may be determined based on an earlier obtained pair of stereo images. The depth image may be refined based on predictions of an earlier stereo image and a later obtained stereo image. Depth information for an environment around a vehicle may be obtained. The depth information may characterize distances between the vehicle and the environment around the vehicle. A spherical depth map may be generated from the depth information. Maneuver controls for the vehicle may be provided based on the spherical depth map.

Provided is a method for three-dimensional imaging a plant in an indoor agricultural environment having an ambient light power spectrum that differs from a power spectrum of natural outdoor light. The method comprises directing a spatially separated stereo pair of cameras at a scene including the plant, illuminating the scene with a non-uniform pattern provided by a light projector utilizing light in a frequency band having a lower than average ambient intensity in the indoor agricultural environment, filtering light entering image sensors of each of the cameras with filters which selectively pass light in the frequency band utilized by the light projector, capturing an image of the scene with each of the cameras to obtain first and second camera images, and generating a depth map including a depth value corresponding to each pixel in the first camera image.

Provided is a method for three-dimensional imaging a plant in an indoor agricultural environment having an ambient light power spectrum that differs from a power spectrum of natural outdoor light. The method comprises directing a spatially separated stereo pair of cameras at a scene including the plant, illuminating the scene with a non-uniform pattern provided by a light projector utilizing light in a frequency band having a lower than average ambient intensity in the indoor agricultural environment, filtering light entering image sensors of each of the cameras with filters which selectively pass light in the frequency band utilized by the light projector, capturing an image of the scene with each of the cameras to obtain first and second camera images, and generating a depth map including a depth value corresponding to each pixel in the first camera image.

A depth image generation apparatus is disclosed including a light source for generating light to be emitted toward an object in order to solve an SNR problem caused by resolution degradation and an insufficient amount of received light, while not increasing a light-emitting amount when photographing a remote object; a first optical system for emitting a dot pattern at the object, the light generated by the light source; an image sensor for receiving light reflected from the object and converting the light into an electrical signal; an image processor for acquiring depth data through the electrical signal; and a control unit connected to the light source, the first optical system, the image sensor and the image processor, where the control unit controls the first optical system so as to scan the object by moving the dot pattern in a preset pattern.

A depth image generation apparatus is disclosed including a light source for generating light to be emitted toward an object in order to solve an SNR problem caused by resolution degradation and an insufficient amount of received light, while not increasing a light-emitting amount when photographing a remote object; a first optical system for emitting a dot pattern at the object, the light generated by the light source; an image sensor for receiving light reflected from the object and converting the light into an electrical signal; an image processor for acquiring depth data through the electrical signal; and a control unit connected to the light source, the first optical system, the image sensor and the image processor, where the control unit controls the first optical system so as to scan the object by moving the dot pattern in a preset pattern.

One or more images of an object, each from a respective viewpoint, may be captured at a camera at a mobile computing device. The images may be compared to reference data to identify a difference between the images and the reference data. Image capture guidance may be provided on a display screen for capturing another one or more images of the object that includes the identified difference.

One or more images of an object, each from a respective viewpoint, may be captured at a camera at a mobile computing device. The images may be compared to reference data to identify a difference between the images and the reference data. Image capture guidance may be provided on a display screen for capturing another one or more images of the object that includes the identified difference.

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.