Abstract: An encoder according to one aspect of the present disclosure encodes a block of an image, and includes a processor and memory connected to the processor. Using the memory, the processor partitions a block into a plurality of sub blocks and encodes a sub block included in the plurality of sub blocks in an encoding process including at least a transform process or a prediction process. The block is partitioned using a multiple partition including at least three odd-numbered child nodes and each of a width and a height of each of the plurality of sub blocks is a power of two.

Abstract: In some examples, a method includes using at least one processor, accessing image data representing an image of a face of a user, identifying a facial feature of the user using the image data, using the at least one processor, automatically matching the facial feature to a matched pattern of a plurality of patterns, based on configured pattern lookup rules, identifying a product depiction, from a plurality of product depictions stored in product database, based on the matched pattern of the plurality of patterns, and causing display of the product depiction on a user interface.

Abstract: A dynamic anatomic atlas is disclosed, comprising static atlas data describing atlas segments and dynamic atlas data comprising information on a dynamic property which information is respectively linked to the atlas segments.

Abstract: A determination system includes an imaging data acquisition device that captures an image of a printed surface of a printed product to acquire imaging data of the captured image, and a determination device that determines a printing method used to produce the printed surface of the printed product for capturing an image by the imaging data acquisition device. The determination device selects a determination area included in the captured image, extracts a determination end image from a portion around an end portion of a black determination image included in the determination area, acquires difference data that is a difference in gradation between two colors among gradation data of RBG colors of the extracted determination end image, acquires a determination value for determining a printing method used to produce the printed surface of the printed product, and determines a printing method used to produce the printed surface of the printed product.

Abstract: Various methods and systems are provided for image processing for multiple cameras. In one embodiment, a method comprises acquiring image frames with a plurality of image frame sources configured with different acquisition settings, processing the image frames based on the different acquisition settings to generate at least one final image frame, and outputting the at least one final image frame. In this way, information from different image frame sources such as cameras may be leveraged to achieve increased frame rates with improved image quality and a desired motion appearance.

Abstract: A method for generating training examples for a product recognition model is disclosed. The method includes capturing images of a product using an array of cameras. A product identifier for the product is associated with each of the images. A bounding box for the product is identified in each of the images. The bounding boxes are smoothed temporally. A segmentation mask for the product is identified in each bounding box. The segmentation masks are optimized to generate an optimized set of segmentation masks. A machine learning model is trained using the optimized set of segmentation masks to recognize an outline of the product. The machine learning model is run to generate a set of further-optimized segmentation masks. The bounding box and further-optimized segmentation masks from each image are stored in a master training set with its product identifier as a training example to be used to train a product recognition model.

Abstract: This application relates to the field of artificial intelligence technologies, and in particular, to a training method of an image-text matching model, a bi-directional search method, and a relevant apparatus. The training method includes extracting a global feature and a local feature of an image sample; extracting a global feature and a local feature of a text sample; training a matching model according to the extracted global feature and local feature of the image sample and the extracted global feature and local feature of the text sample, to determine model parameters of the matching model; and determining, by the matching model, according to a global feature and a local feature of an inputted image and a global feature and a local feature of an inputted text, a matching degree between the image and the text.

Abstract: A method of an optical sensor device used for detecting a color of a specific surface of an object includes: providing a sensor array having a plurality of pixel units each for receiving light reflected from the specific surface to generate a sensed pixel value; using the sensor array to generate a specific image formed by a plurality of sensed pixel values; determining whether the specific image is similar to a first solid color image corresponding to a first color according to the plurality of sensed pixel values of the specific image; and determining to execute a distance detection operation to calculate a specific distance from the optical sensor device to the specific surface according to a color saturation value of the first color in the specific image when it is determined that the specific image is similar to the first solid color image corresponding to the first color.

Abstract: An apparatus configured to be head-worn by a user, includes: a screen configured to present graphics for the user; a camera system configured to view an environment in which the user is located; and a processing unit coupled to the camera system, the processing unit configured to: obtain locations of features for an image of the environment, wherein the locations of the features are identified by a neural network; determine a region of interest for one of the features in the image, the region of interest having a size that is less than a size of the image; and perform a corner detection using a corner detection algorithm to identify a corner in the region of interest.

Abstract: The invention is a system for color analysis, which comprises a hand-held device and a working platform. The hand-held device is provided with a camera and installed with analysis software. The work platform is placed with an object to be tested, a standard color carrier is installed at both front and rear sides or at both left and right sides of the object to be tested, a positioning frame extends upward around the working platform, the positioning frame and the working platform are mutually formed an inclination angle, and the positioning frame is used to fix the hand-held device. In this way, the camera can shoot the working platform in an inclined direction, and then the analysis software is used to compare a color difference between the object to be tested and the standard color carrier to obtain analysis result of the object to be tested.

Abstract: Disclosed is an imaging system and associated methods for mapping in-focus image data from two-dimensional (“2D”) images of a scene to a three-dimensional (“3D”) model of the scene. The imaging system receives the 2D images and the 3D model, determines the depth of field (“DOF”) and the field of view (“FOV”) for each 2D image, and selects a subset of 3D model constructs that form the FOV and are within the DOF of a particular 2D image. The imaging system determines pixels of the particular 2D image that represent a same set of points in the scene as the subset of 3D model constructs, and maps the visual characteristics from those pixels to non-positional elements of the subset of 3D model constructs.

Abstract: At a first time point, a first light capturing device at a first spatial location in a three-dimensional (3D) space captures first light rays from light sources located at designated spatial locations on a viewer device in the 3D space. At the first time point, a second light capturing device at a second spatial location in the 3D space captures second light rays from the light sources located at the designated spatial locations on the viewer device in the 3D space. Based on the first light rays captured by the first light capturing device and the second light rays captured by the second light capturing device, at least one of a spatial position and a spatial direction, at the first time point, of the viewer device is determined.

Abstract: An imaging system and method for microbial growth detection, counting or identification. One colony may be contrasted in an image that is not optimal for another type of colony. The system and method provides contrast from all available material through space (spatial differences), time (differences appearing over time for a given capture condition) and color space transformation using image input information over time to assess whether microbial growth has occurred for a given sample.

Abstract: A crop generation system determines multiple types of saliency data and multiple crop candidates for an image. Multiple region of interest (“ROI”) ensembles are generated, indicating locations of the salient content of the image. For each crop candidate, the crop generation system calculates an evaluation score. A set of crop candidates is selected based on the evaluation scores.

Abstract: A depth estimation method and apparatus are provided. The depth estimation method includes obtaining an image from an image sensor comprising upper pixels, each comprising N sub-pixels, obtaining N sub-images respectively corresponding to the N sub-pixels from the image, obtaining a viewpoint difference between the N sub-images using a first neural network, and obtaining a depth map of the image based on the viewpoint difference using a second neural network.

Abstract: A method and system can include processing title and title opinion document images to generate text information. Trained models may generate data objects representative of period of time during which certain rights to a property exist. The trained models may also generate rules for modifying the data objects and interrelating the data objects to each other. In some examples, a confidence level can be generated and will reflect a likelihood of a data object including correct information. The modified and interrelated data objects may be used to generate a navigable interface which includes a current title status for a property and a navigable chain of title reflecting historical rights to the property.

Abstract: A circular sign candidate extraction device includes: a memory; and a processor coupled to the memory, the processor being configured to perform processing, the processing including: detecting a circle from a captured image; specifying an annular region surrounded by the detected circle and a concentric circle, the concentric circle being a circle having a radius different from the detected circle; setting one or more pixels among pixels included in the annular region as determination pixels; and extracting a circular sign candidate from the detected circle in accordance with comparison between a color of the determination pixel and a predetermined color.

Abstract: There is disclosed a system for automatically detecting an irregularity on a pipe. The system includes a camera arranged at an external surface of the pipe, the camera being configured to capture a Red, Green and Blue (RBG) image of a region of a pipe. One or more hardware processors are in communication with the camera and are configured to: convert the RGB image to a modified image; split the modified image into a plurality of components; generate a binary image via performing a thresholding operation which utilizes the plurality of components; and detect the irregularity on the pipe via performing a feature extraction process on the binary image. Also disclosed and described is a related method.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to detecting text in images. In some embodiments, a system for detecting text in images comprises a database configured to store images and a control circuit configured to retrieve an image, generate, based on the image, a collection of augmented images, detect characters in each of the augmented images, generate bounding boxes for the characters in each of augmented images, recognize the characters in each of the augmented images, select, based on the recognition of the characters in each of the augmented images, candidate characters, wherein the candidate characters are selected based on consistency of the recognition of the characters in each of the augmented images, detect, for the image, a color associated with the characters, and store, in the database, the image, the candidate characters, and the color associated with the characters.

Abstract: In one embodiment, a method includes receiving, by a defect detector module, an image of a physical object and classifying, by the defect detector module, one or more first features from the image of the physical object into one or more first classifications using one or more machine learning algorithms. The method further includes analyzing, by the defect detector module, the one or more first classifications and determining, by the defect detector module, that the physical object comprises a defect based on analyzing the one or more first classifications.