Disclosed is a care device recommendation server providing a service for recommending a skin care device for a user, the care device recommendation server including: a data management unit configured to obtain face images of the user from a shin measurement device including a camera and a display; a skin condition determination unit configured to determine a first skin condition of the user corresponding to a first time point at which the face images are obtained, based on the obtained the face images; a care device recommendation unit configured to determine the skin care device for the user among a plurality of care devices included in a care device DB based on the determined first skin condition; a care device control value-providing unit configured to provide a first control value of the skin care device corresponding to the first skin condition to each of a user terminal of the user and the skin measurement device; a care device control unit configured to remotely control the care device such that the skin care device is driven by the control value; and a history provision unit configured to provide information about a previous skin condition of the user, which corresponds to each of the face images of the user obtained from the data management unit, to the user terminal.

Disclosed is a system and associated methods for generating and rendering a polyhedral point cloud that represents a scene with multi-faceted primitives. Each multi-faceted primitive stores multiple sets of values that represent different non-positional characteristics that are associated with a particular point in the scene from different angles. For instance, the system generates a multi-faceted primitive for a particular point of the scene that is captured in first capture from a first position and a second capture from a different second position. Generating the multi-faceted primitive includes defining a first facet with a first surface normal oriented towards the first position and first non-positional values based on descriptive characteristics of the particular point in the first capture, and defining a second facet with a second surface normal orientated towards the second position and second non-positional values based on different descriptive characteristics of the particular point in the second capture.

To enable a high quality HDR video communication, which can work by sending corresponding LDR images potentially via established LDR video communication technologies, which works well in practical situations, applicant has invented a HDR video decoder (600, 1100) arranged to calculate a HDR image (Im_RHDR) based on applying to a received 100 nit standard dynamic range image (Im_RLDR) a set of luminance transformation functions, the functions comprising at least a coarse luminance mapping (FC), which is applied by a dynamic range optimizer (603), and a mapping of the darkest value (0) of an intermediate luma (Y′HPS), being output of the dynamic range optimizer, to a received black offset value (Bk_off) by a range stretcher (604), the video decoder comprising a gain limiter (611, 1105) arranged to apply an alternate luminance transformation function to calculate a subset (502) of the darkest luminances of the HDR image, from corresponding darkest lumas (Y′_in) of the standard dynamic range image.

Systems and methods for color selection are provided and include a web server configured to communication computer executable instructions to a mobile device that configure the mobile device to access a social media platform, retrieve a plurality of images from the social media platform, determine a dominant color for each image of the plurality of images using different sample rates for different pixel groups based on how close each pixel group is to the center of the image, determine a closest matching paint color for the dominant color for each image, and display at least one of a color name and a color code associated with the closest matching paint color for the dominant color for each image.

One aspect of the present disclosure relates to a generation method for a training dataset, comprising: capturing, by one or more processors, a target object to which a marker unit recognizable under a first illumination condition is provided; and acquiring, by the one or more processors, a first image where the marker unit is recognizable and a second image obtained by capturing the target object under a second illumination condition.

In some aspects, the techniques described herein relate to systems, methods, and computer readable media for data pre-processing for stereo-temporal image sequences to improve three-dimensional data reconstruction. In some aspects, the techniques described herein relate to systems, methods, and computer readable media for improved correspondence refinement for image areas affected by oversaturation. In some aspects, the techniques described herein relate to systems, methods, and computer readable media configured to fill missing correspondences to improve three-dimensional (3-D) reconstruction. The techniques include identifying image points without correspondences, using existing correspondences and/or other information to generate approximated correspondences, and cross-checking the approximated correspondences to determine whether the approximated correspondences should be used for the image processing.

Systems and methods for movement detection are provided. In one example embodiment, a computer-implemented method includes obtaining image data and range data representing a scene external to an autonomous vehicle, the image data including at least a first image and a second image that depict the scene. The method includes identifying a set of corresponding image features from the image data, the set of corresponding image features including a first feature in the first image having a correspondence with a second feature in the second image. The method includes determining a respective distance for each of the first feature and the second feature based at least in part on the range data. The method includes determining a velocity associated with a portion of a scene represented by the set of corresponding image features based at least in part on the respective distance for the first feature and the second feature.

There is a need to accurately and dynamically evaluate an individual's risk associated with the transmission or contraction of a disease. This need can be addressed, for example, by generation of a real-time or near real-time predicted disease score for an associated user. In one example, a method includes receiving a video stream data object depicting a visual representation of a target user; processing the video stream data object to generate a protective covering indication with respect to the target user; processing the video stream data object to generate a spatial proximity determination score with respect to the target user; processing the protective covering indication and spatial proximity determination score to generate a predicted disease score associated with the target user; and providing an augmented reality video stream data object configured to depict the visual representation of the target user and the predicted disease score.

A network for category-level 6D pose and size estimation, including a 3D-OCR module for 3D Orientation-Consistent Representation, a GeoReS module for Geometry-constrained Reflection Symmetry, and a MPDE module for Mirror-Paired Dimensional Estimation; wherein the 3D-OCR module and the GeoReS module are incorporated in parallel; the 3D-OCR module receives a canonical template shape including canonical category-specific keypoints; the GeoReS module receives an original input depth observation including pre-processed predicted category labels and potential masks of the target instances; the MPDE module receives the output from the GeoReS module as well as the original input depth observation; and the network outputs the estimation results based on the output of the MPDE module, the output of the 3D-OCR module, as well as the canonical template shape. Also provided are corresponding systems and methods.

An image capturing method and a terminal device are provided. The method includes entering a camera application to start a lens and display a viewfinder interface, converting an original image captured by the lens into a red-green-blue (RGB) image, and decreasing luminance of the RGB image to be less than first luminance or increasing the luminance of the RGB image to be greater than second luminance, to obtain a first image; converting the RGB image into N frames of high-dynamic-range (HDR) images, and fusing color information of pixels in any same location on the first image and the N frames of HDR images to obtain a final image.