Apparatus and methods for the stitch zone calculation of a generated projection of a spherical image. In one embodiment, a computing device is disclosed which includes logic configured to: obtain a plurality of images; map the plurality of images onto a spherical image; re-orient the spherical image in accordance with a desired stitch line and a desired projection for the desired stitch line; and map the spherical image to the desired projection having the desired stitch line. In a variant, the desired stitch line is mapped onto an optimal stitch zone, the optimal stitch zone characterized as a set of points that defines a single line on the desired projection in which the set of points along the desired projection lie closest to the spherical image in a mean square sense.

An apparatus includes a projection unit configured to project a video image, a capturing unit configured to capture an image, an identification unit configured to identify a shape of a surface onto which the video image is to be projected, based on the captured image, an inference unit configured to infer a viewpoint position and an attitude of a viewer of the video image based on the captured image, a correction unit configured to correct the video image based on the shape of the surface and the viewpoint position and the attitude of the viewer, and a control unit configured to control the projection unit to project the corrected video image.

A projection system and method for depth-based projection of image-based content is provided. The projection system receives a sequence of image frames to be projected on a physical surface of a three-dimensional (3D) structure. The projection system controls a depth sensor to acquire depth data associated with the physical surface and feeds a first input including the acquired depth data and a first image frame of the received sequence of image frames to a neural network-based model. The projection system further receives a set of geometric correction values as a first output of the neural network-based model for the fed first input and modifies the first image frame based on the received set of geometric correction values. The projection system further controls the illumination circuitry to project the modified first image frame onto the physical surface.

A system allows a user to create new designs for apparel and preview these designs before manufacture. Software and lasers are used in finishing apparel to produce a desired finishing pattern or other design. The system provides three-dimensional previews of their designs on a mannequin or other surface, using light projection techniques.

Systems and methods described herein relate to training a machine-learning-based monocular depth estimator. One embodiment selects a virtual image in a virtual dataset, the virtual dataset including a plurality of computer-generated virtual images; generates, from the virtual image in accordance with virtual-camera intrinsics, a point cloud in three-dimensional space based on ground-truth depth information associated with the virtual image; reprojects the point cloud back to two-dimensional image space in accordance with real-world camera intrinsics to generate a transformed virtual image; and trains the machine-learning-based monocular depth estimator, at least in part, using the transformed virtual image.

A system allows a user to create new designs for apparel and preview these designs before manufacture. Software and lasers are used in finishing apparel to produce a desired wear pattern or other design. Users may collaborate while designing the apparel and designate what items should belong in specific collections. Users may also use an assortment builder tool to search a database of products according to one or more search parameters to select a garment with a finishing pattern.

One embodiment provides a method, including: identifying, using data obtained from at least one sensor associated with an information handling device, a multi-planar orientation of a non-flat display surface of the information handling device and a spatial orientation of the information handling device with respect to a user's gaze position; determining, using a processor and based on the identifying, a distortion of at least one object displayed on the non-flat display surface; and adjusting at least one aspect of the non-flat display surface to correct the distortion. Other aspects are described and claimed.

Embodiments of the present disclosure disclose a method and device for vertical correction of a panoramic image, an electronic apparatus and a storage medium. The method includes extracting a set of straight line segments from the panoramic image, where an included angle between each straight line segment in the set of straight line segments and a current vertical direction of the panoramic image is less than a preset angle. The method further includes determining a set of target points by mapping the set of straight line segments on a unit sphere of the panoramic image. The method also includes determining an equatorial plane based on the set of target points and the center of the unit sphere and determining a vertical correction matrix based on the equatorial plane and a unit vector of the current vertical direction. The method additionally includes performing the vertical correction on the panoramic image using the vertical correction matrix.

A method comprising steps: (a) providing an image; (b) opening the image in a photo editing software program; (c) importing a skullcap shape having four equal triangular curve portions into the photo editing software program; (d) editing the image to match the skullcap shape and triangular curve portions; (e) printing the edited image to a medium; (f) separating the four triangular curve portions of the printed image; and (g) sewing the four separate triangular curve portions into a skullcap.

A projection apparatus includes a matrix expression generation unit which generates viewpoint correction matrices used for a conversion calculation on each of the projection surfaces for an image to be projected, a mask generation unit which generates correction mask data indicating regions corresponding to the viewpoint correction matrices generated by the matrix expression generation unit for the image, and a projection control unit which executes the conversion calculation on the image using each viewpoint correction matrix generated for each corresponding region in the correction mask data generated by the mask generation unit, and thereafter controls the projection unit to project the image.