Abstract: A geospatial modeling system may include a memory and a processor cooperating therewith to generate a three-dimensional (3D) geospatial model including geospatial voxels based upon a plurality of geospatial images, obtain a newly collected geospatial image, and determine a reference geospatial image from the 3D geospatial model using Artificial Intelligence (AI) and based upon the newly collected geospatial image. The processor may further align the newly collected geospatial image and the reference geospatial image to generate a predictively registered image, and update the 3D geospatial model based upon the predictively registered image.

Abstract: Systems, methods and apparatuses to classify and/or control content passing through a memory device. For example, a portion of a media stream received from a content source can be buffered in a memory device a predetermined time before presentation. An artificial neural network (ANN) in the memory device can identify a region in the buffered portion and analyze the region to determine a classification of content in the region. Within the memory device, the content in the region can be transformed according to a preference specified for the classification. For example, unwanted or objectionable content can be masked, distorted, skipped, replaced, and/or filtered. A modified version of the portion is generated from transforming the content in the region as output for presentation.

Abstract: An example wearable display system can be capable of determining a user interface (UI) event with respect to a virtual UI device (e.g., a button) and a pointer (e.g., a finger or a stylus) using a neural network. The wearable display system can render a representation of the UI device onto an image of the pointer captured when the virtual UI device is shown to the user and the user uses the pointer to interact with the virtual UI device. The representation of the UI device can include concentric shapes (or shapes with similar or the same centers of gravity) of high contrast. The neural network can be trained using training images with representations of virtual UI devices and pointers.

Abstract: A method for image processing may include: obtaining an original image of a first style, the original image being generated by a first imaging device; obtaining a target transformation model; and generating a transferred image of a second style by transferring the first style of the original image using the target transformation model. The second style may be substantially similar to a target style of one or more other images generated by a second imaging device. The second style may be different from the first style.

Abstract: Techniques related to the detection or identification of biological cells or substances.

Abstract: An information processing apparatus for configuring a signage device acquires layout information including position information of at least one signage device in a target area and a floor plan which enables identification of placement of at least one fixture placed in the target area, and content information associated with content to be displayed on the signage device. The information processing apparatus displays an icon corresponding to the signage device at a position corresponding to position information in the floor plan. On receiving a selection of the icon from a user, the information processing apparatus displays content information set in the signage device or content information to be set in the signage device, which enhances the user-friendliness in checking or setting up configuration details.

Abstract: A driving method, suitable for a multimedia system including a head-mounted device (HMD), includes the following operations: retrieving human factor data from a storage device, a radio signal, or an image; and according to the human factor data, automatically adjusting software for driving the HMD or hardware components of the multimedia system.

Abstract: Systems and methods for updating a classification model of a neural network. The methods include selecting, as a set of landmarks, a limited number of data from a set of historical data used to train a classification model. Additionally, the methods generate new training data from recently collected data. Further, the methods update the classification model with the new training data and the set of landmarks to obtain an updated classification model having a loss function configured to capture similarities in the new training data and remember similarities in the historical data represented by the set of landmarks within a predefined tolerance.

Abstract: A process includes obtaining a set of images compositable to depict different design configurations; providing a first user interface by which members of the set are overlaid responsive to user inputs to depict different design configurations; obtaining a first design configuration specified via the first user interface; and providing a second user interface depicting a field of view having a first portion depicting the first design configuration and a second porting depicting a second design configuration, the second user interface being operative to adjust allocation in pixel space of the field of view between the first portion and the second portion responsive to user input.

Abstract: An image processing device having a processor coupled to a memory. The processor is programmed to process two or more media formats stored in the memory, each media format is made up of one or more digital image layers that includes non-transparent pixels and may include transparent pixels. The processor is programmed to: set the non-transparent pixels in each of the digital image layer of the two or more media formats to a contrast state, set pixels stored in an off-screen data buffer of the memory to pixels corresponding to a predetermined color scheme, apply an image function to each media format that is drawn to the off-screen data buffer so as to allow the plurality of overlapping media formats to be displayed on the display screen as see through.

Abstract: A display system includes a display device. The display device is arranged to receive a video signal and a control signal from a host system, and includes a processing circuit and a display screen, wherein the processing circuit is arranged to process an original frame corresponding to the video signal according to the control signal, to generate a magnified frame, and generate a processed frame according to the magnified frame and the original frame, and the display screen is coupled to the processing circuit, and is arranged to display the processed frame.

Abstract: A textual properties model is used to infer values for certain font properties of interest given certain text-related data, such as rendered text images. The model may be used for numerous purposes, such as aiding with document layout, identifying font families that are similar to a given font families, and generating new font families with specific desired properties. In some embodiments, the model is trained from a combination of synthetic data that is labeled with values for the font properties of interest, and partially-labeled data from existing “real-world” documents.

Abstract: Image stylization is based on a learning network. A learning network is trained with a plurality of images and a reference image with a particular texture style. A plurality of different sub-networks of the learning network is trained, respectively. Specifically, one of the sub-networks is trained to extract one or more feature maps from the source image and transform the feature maps with the texture style applied thereon to a target image. Each of the feature maps indicates part of feature information of the source image. Another sub-network is trained to apply a specified texture style to the extracted feature maps, such that the target image generated based on the processed feature maps can embody the specified texture style.

Abstract: A server of a generative adversarial network (GAN) for color selection; generates a training set of color palettes. A color palette generator of the server generates a first set of color palettes based on the training set of color palettes. The first set of color palettes may be compared with a reference set of color palettes to predict a curated set of color palettes. Colors from the curated set of color palettes may be removed that are within a predetermined distance from one another in a color space. The GAN may be validated by performing cluster analysis to determine outlier latent dimensions to be changed for the color selection by the GAN. Proposed color palettes may be generated based on the GAN to be displayed on a display device.

Abstract: First image data representing a first human wearing a first article of clothing may be received. The first image data, when rendered on a display, may include a first photometric artifact. A first generator network may be used to generate second image data from the first image data. The first photometric artifact may be removed from the second image data. A second generator network may be used to generate third image data from the second image data, the third image data representing the first human in a different pose relative to the first image data. Fourth image data representing the first article of clothing segmented from the first human may be generated and displayed on a display.

Abstract: A display apparatus includes a display panel, a first coordinate calculator, a second coordinate calculator and a gamma setter. The display panel includes a first display area and a second display area. The first coordinate calculator is configured to calculate color coordinates of first image data of the first display area. The second coordinate calculator is configured to calculate color coordinates of second image data of the second display area. The gamma setter is configured to adjust luminance of the first image data, the color coordinates of the first image data, luminance of the second image data and the color coordinates of the second image data.

Abstract: Images of various views of objects can be captured. An object mesh structure can be created based at least in part on the object images. The object mesh structure represents the three-dimensional shape of the object and includes a mesh with mesh elements. The mesh elements are assigned views first from a subset of views to texture large contiguous portions of the object from relatively few views. Portions that are not textured from the subset views are textured using the full set of views, such that all mesh elements are assigned views. The views first assigned from the subset of views and the views then assigned from the full plurality of views can be packaged into a texture atlas. These texture atlas views can be packaged with mapping data to map the texture atlas views to their corresponding mesh elements. The texture atlas and the object mesh structure can be sent to a client device to render a representation of the object.

Abstract: A decoder unit is configured to decode a plurality of texels in accordance with a texel request, the plurality of texels being encoded across one or more blocks of encoded texture data each encoding a block of texels, and includes a first set of one or more decoders, each of the first set of decoders being configured to decode n texels from a single received block of encoded texture data; a second set of or more decoders, each of the second set of decoders being configured to decode p texels from a single received block of encoded texture data, where p<n; and control logic configured to allocate blocks of encoded texture data to the decoders in accordance with the texel request.

Abstract: An augmented reality display system can include a partially transparent eyepiece, an ambient light sensor, and an image input device. The image input device can include a light source and a spatial light modulator. The system can also include a controller that determines that no virtual content is being displayed to the user and compares the ambient light to display light to determine if a light source shutoff criterion is satisfied. If the light source shutoff criterion is satisfied, the controller can turn off the light source.

Abstract: An electronic device includes an information acquisition unit, a display information determination unit, and a display control unit. The information acquisition unit acquires first pulse wave information indicating a pulse wave of a part of a body based on image information of the body in a first image obtained by imaging at least the part of the body, and acquires second pulse wave information indicating a pulse wave of a part of the body based on image information of the body in a second image obtained by imaging the part of the body after the first image has been obtained. The display information determination unit determines a display range of a display color of a display image or brightness corresponding to a blood flow variation of a part of the body based on first pulse wave information and second pulse wave information. The display control unit controls display of the display image by the display color determined based on the display range or brightness and the second pulse wave information.