According to a general aspect, a method can include receiving a photo of a virtual conference participant, and a depth map based on the photo, and generating a plurality of synthesized images based on the photo. The plurality of synthesized images can have respective simulated gaze directions of the virtual conference participant. The method can also include receiving, during a virtual conference, an indication of a current gaze direction of the virtual conference participant. The method can further include animating, in a display of the virtual conference, an avatar corresponding with the virtual conference participant. The avatar can be based on the photo. Animating the avatar can be based on the photo, the depth map and at least one synthesized image of the plurality of synthesized images, the at least one synthesized image corresponding with the current gaze direction.

A material data collection system allows capturing of material data. For example, the material data collection system may include digital image data for materials. The material data collection system may ensure that captured digital image data is properly aligned, so that material data may be easily recalled for later use, while maintaining the proper alignment for the captured digital image. The material data collection system may include using a capture guide, to provide cues on how to orient a mobile device used with the material data collection system.

A method and a system for generating a composite video feed for a geographical area are disclosed. A video of the geographical area, captured by a camera, of an aerial platform is received. The video includes metadata indicative of location information, which is used to identify the coordinates of the geographical area. An image that is adjacent to the geographical area is received from the geographical information system and is transformed according to the metadata. The coordinates of the geographical area are used to determine an area with the image. The video is embedded in the area by matching the area with the coordinates of the geographical area, where the edges of the video correspond to the boundaries of the area. A composite video feed, including the video embedded along with the image, is generated and a video player displays the composite video feed.

Systems and methods for digitized document image data spillage recovery are provided. One or more memories may be coupled to one or more processors, the one or more memories including instructions operable to be executed by the one or more processors. The one or more processors may be configured to capture an image; process the image through at least a first pass to generate a first contour; remove a preprinted bounding region of the first contour to retain text; generate one or more pixel blobs by applying one or more filters to smudge the text; identify the one or more pixel blobs that straddle one or more boundaries of the first contour; resize the first contour to enclose spillage of the one or more pixel blobs; overlay the text from the image within the resized contour; and apply pixel masking to the resized contour.

An optical imaging system for imaging a target during a medical procedure, the optical imaging system involving a first camera for capturing a first image of the target, a second wide-field camera for capturing a second image of the target, at least one optional path folding mirror disposed in an optical path between the target and a lens of the second camera, and a processor for receiving the first image and the second image, the processor configured to apply an image transform to one of the first image and the second wide-field image and combine the transformed image with the other one of the images to produce a stereoscopic image of the target.

Methods and apparatus are disclosed for implementing data augmentation within a storage controller of a data storage device based on machine learning data read from a non-volatile memory (NVM) array of a memory die. Some particular aspects relate to configuring the storage controller to generate augmented versions of training images for use in training a Deep Learning Accelerator of an image recognition system by rotating, translating, skewing, cropping, etc., a set of initial training images obtained from a host device and stored in the NVM array. Other aspects relate to controlling components of the memory die to generate noise-augmented images by, for example, storing and then reading training images from worn regions of the NVM array to inject noise into the images. Data augmentation based on data read from multiple memory dies is also described, such as image data spread across multiple NVM arrays or multiple memory dies.

Systems and methods for spatial analysis of analytes are provided. A data structure is obtained comprising an image, as an array of pixel values, of a sample on a substrate having a identifier, fiducial markers and a set of capture spots. The pixel values are used to identify derived fiducial spots. The substrate identifier identifies a template having reference positions for reference fiducial spots and a corresponding coordinate system. The derived fiducial spots are aligned with the reference fiducial spots using an alignment algorithm to obtain a transformation between the derived and reference fiducial spots. The transformation and the template corresponding coordinate system are used to register the image to the set of capture spots. The registered image is then analyzed in conjunction with spatial analyte data associated with each capture spot, thereby performing spatial analysis of analytes.

Object overlay for vehicle occupants includes determining that visibility of an object in a view of a vehicle occupant through a transparent surface of the vehicle is degraded, the object being in an environment in which the vehicle travels, selecting from an image repository a reference image of the object, extracting, from the reference image, an image portion comprising an image of a least a portion of the object, transforming the extracted image portion to correspond to the view of the vehicle occupant, the transforming producing a transformed image portion, and displaying the transformed image portion on the transparent surface and interposed in a line-of-sight of the vehicle occupant to the object in the environment such that the transformed image portion overlays at least a portion of the vehicle occupant's view through the transparent surface to the object in the environment.

Systems and methods for spatial analysis of analytes are provided. A data structure is obtained comprising an image, as an array of pixel values, of a sample on a substrate having a identifier, fiducial markers and a set of capture spots. The pixel values are used to identify derived fiducial spots. The substrate identifier identifies a template having reference positions for reference fiducial spots and a corresponding coordinate system. The derived fiducial spots are aligned with the reference fiducial spots using an alignment algorithm to obtain a transformation between the derived and reference fiducial spots. The transformation and the template corresponding coordinate system are used to register the image to the set of capture spots. The registered image is then analyzed in conjunction with spatial analyte data associated with each capture spot, thereby performing spatial analysis of analytes.

A method and system of recognizing and processing object edges and a computer-readable storage medium are provided. The method includes: obtaining an input image, where the input image includes an object with edges, and the edges of the object include a plurality of object vertices; recognizing, through an object vertex recognition model, the input image and obtaining a relative position of each object vertex and a corresponding image vertex thereof; determining an actual position of each object vertex in the input image according to the relative position of each object vertex and the corresponding image vertex thereof; and sequentially connecting adjacent object vertices to form edge lines to obtain the edges of the object with edges in the input image according to the actual position of each object vertex in the input image.