Abstract: A method of identifying an animal may include obtaining a digital image of at least a portion of the animal's nose, identifying a reference point in the digital image from one or more landmarks in the digital image, detecting a plurality of edges in the digital image, the plurality of edges defining a plurality of islands separated by recessed channels, extracting, from the digital image, one or more features characterizing the plurality of islands in relation to the reference point, and comparing the one or more features to a database of extracted features stored in association with known animals.

Abstract: An image search apparatus includes a search processing unit, a first display processing unit, and a second display processing unit. The search processing unit extracts one or more images that meet a search condition, from a plurality of images associated with user accounts. The first display processing unit displays, as a result of search, the one or more images extracted by the search processing unit. The second display processing unit displays a predetermined specific page when, among the one or more images displayed as the result of search, a personally photographed image is operated, the personally photographed image being an image associated with a first-type user account and photographed at a facility corresponding to a second-type user account that is different from the first-type user account, the specific page corresponding to the second-type user account.

Abstract: A living body determination device includes: a light irradiation device that irradiates a measuring object with a first light including a plurality of spectrums; a spectroscopic device that disperses a light at intensity depending on a wavelength and outputs the light; an image acquisition device that receives the light output by the spectroscopic device and outputs image information representing brightness depending on the intensity of the light; and a control unit. The control unit, for each spectrum of the first light, acquires image information with respect to the measuring object from the image acquisition device, based on the image information, selects one or more areas, for each of the areas, acquires spectroscopic information, and based on whether the spectroscopic information satisfies a predetermined condition, determines whether the measuring object is a living body.

Abstract: A computer-implemented method of providing a filter (F) in a neural processing unit comprises: receiving input corresponding to target dimensions (XT, YT) of the filter; receiving input corresponding to sub-filter dimensions (X1 . . . n?, Y1 . . . n?) of each of a plurality of sub-filters (SF1 . . . n) implementable in the neural processing unit; and defining the filter (F) as a combination of the plurality of sub-filters (SF1 . . . n), the combination having dimensions that equate to the target dimensions (XT, YT), and wherein the sub-filter dimensions (X1 . . . n?, Y1 . . . n?) of at least two of the sub-filters in the combination are unequal.

Abstract: Systems, methods and non-transitory computer readable media for exploring images of construction sites by construction stages are provided. For example, a plurality of images of a construction site may be accessed, each image of the plurality of images may correspond to a location in the construction site and a construction stage. In response to a received indication of location and a received indication of a construction stage, an image corresponding to the indicated location and to the indicated construction stage may be selected and presented. In response to a received indication of location and a received indication of a capturing time, an image corresponding to the indicated location and to the indicated capturing time may be selected and presented.

Abstract: The disclosed techniques include at least one computer-implemented method performed by a system. The system can receive a textual query and process query features of the textual query to identify a color profile indicative of a color intent of the query. The system can identify candidate images that at least partially match the desired content and color intent of the query. The system can further order candidate images based in part on a similarity of a candidate color profile for each candidate image with the identified color profile of the query, and output image data indicative of the ordered set of candidate images.

Abstract: This application relates to an image processing method and apparatus, a facial recognition method and apparatus, a computer device, and a readable storage medium.

Abstract: Various techniques are disclosed for systems and methods to provide image resolution enhancement. For example, a method includes: receiving an original image (e.g., a visible light image) of a scene comprising image pixels identified by pixel coordinates; resizing the original image to a larger size, where the resized image is divided into a first plurality of reference blocks; enhancing a resolution of the resized image by iteratively: injecting high frequency data into the resized image, extracting from the resized image a first plurality of matching blocks that meet a mutual similarity condition with respect to the reference block, and adjusting the high frequency data of the reference block based on a correlation between the reference block and the first plurality of matching blocks. A system configured to perform such a method is also disclosed.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for tracking a product item in an automated-checkout store. One of the methods includes receiving, by a computer system, data collected by multiple image sensors, the received data including data associated with a person, identifying, by the computer system based on the received data, multiple features of the person, extracting, by the computer system based on the identified features, data associated with the person from the received data, wherein the extracted data correspond to multiple time periods, and determining, by the computer system, a location of the person in each of the time periods based on the extracted data corresponding to the time period, wherein the determining includes aggregating the extracted data collected by different image sensors based at least in part on a location and a line of sight of each of the image sensors.

Abstract: Systems, methods, and non-transitory computer-readable media are disclosed for determining a glyph and a font from a vector outline by applying various combinations of hash-based querying, path-descriptor matching, or anchor-point matching. For example, the disclosed systems can select a subset of candidate glyphs for a vector outline based on (i) comparing hash keys of candidate glyphs with a point-order-agnostic hash key corresponding to the vector outline and (ii) comparing a path descriptor for a primary path of the vector outline to path descriptors corresponding to candidate glyphs. By further comparing anchor points between the vector outline and the subset of candidate glyphs, the disclosed systems can select both a glyph and a font matching the vector outline.

Abstract: Images are tagged with values in an image data hierarchy that is most subjective at its top level and least subjective at its bottom level, such as a hierarchy including style, type, and features for clothing. A user preference hierarchy is determined from user response to images that are tagged. Tagged images may be generated by processing them with machine learning models trained to determine values for images. Product records including images and other data are analyzed to generate attribute vectors that are encoded to generate product vectors. Products are clustered according to their product vectors. Images of products within a cluster are clustered according to composition and groups of images are selected from image clusters for soliciting feedback regarding user preference for products of a cluster. Feedback is used to train a user preference model to estimate user affinity for a product having a given product vector.

Abstract: Using a simple cue to reduce a number of sequential frames included in a video that needs to be analyzed by an artificial neural network to predict information corresponding to a projectile depicted within the video is provided. A timing of the simple cue associated with the video is detected. The number of sequential frames within the video is reduced down to only those frames that are within a specified range of the simple cue. The artificial neural network is used to analyze the reduced number of sequential frames. The information corresponding to the projectile is predicted based on analyzing the reduced number of sequential frames using the artificial neural network.

Abstract: An image processing apparatus including a unit configured to acquire a current image from an inputted video and a background model which comprises a background image and foreground/background classification information of visual elements; a unit configured to determine first similarity measures between visual elements in the current image and the visual elements in the background model; and a unit configured to classify the visual elements in the current image as the foreground or the background according to the current image, the background image in the background model and the first similarity measures. Wherein, the visual elements in the background model are the visual elements whose classification information is the background and which neighbour to corresponding portions of the visual elements in the current image. Accordingly, the accuracy of the foreground detection could be improved.

Abstract: A method relating to an image fusion includes acquiring a thermal infrared image and a visible image. The method also includes receiving a fusion parameter corresponding to a color space and generating, based on the fusion parameter, a fused image of the thermal infrared image and the visible image. The method further includes receiving a regulation parameter, the regulation parameter including a color scheme or a partial contrast, and adjusting the fused image according to the regulation parameter.

Abstract: A computer-implemented method of detecting logos in a graphical rendering may comprise detecting, using a first and a second trained object detector, logos in the graphical rendering and outputting a first and a second list of detections and filtering, using at least a first and a second prior performance-based filter, the received first and second lists of detections into a first group of kept detections, a second group of discarded detections and a third group of detections. Detections in the third group of detections may be clustered in at least one cluster comprising detections that are of a same class and that are generally co-located within the electronic image. A cluster score may then be assigned to each cluster. A set of detections of logos in the graphical rendering may then be output, the set comprising the detections in the first group and a detection from each of the clusters whose assigned cluster score is greater than a respective threshold.

Abstract: The present disclosure relates to an image retrieval method and apparatus. The method includes: obtaining an image group including a query image and at least one candidate image; calculating an intermediate similarity between any two images in the image group; performing multi-scale feature fusion based on the intermediate similarity between the any two images to obtain a final similarity between the query image and each candidate image; and determining a target image corresponding to the query image from each candidate image based on the final similarity. The present disclosure can improve precision and robustness of image retrieval.

Abstract: In a measurement device, an image acquisition unit acquires a first image generated by imaging an object to be measured in a first imaging state and acquires one or more second images generated by imaging the object in one or more second imaging states. A specified point setting unit sets a specified point on the first image. A three-dimensional (3D) shape restoration unit restores a 3D shape of the object by using a plurality of images including the second image determined to include a point corresponding to the specified point. A reference dimension setting unit sets a reference dimension on the first image or the 3D shape. A measurement unit measures the object on the basis of the 3D shape, the specified point, and the reference dimension.

Abstract: An image selector selects images for visual similarity in some aspects and visual distinction in other aspects. A user submits a query to a search engine. Images identified by the search engine as relevant to the query are clustered into clusters having at least one similar attribute. Selection mechanisms organize images selected from each cluster based on a similarity metric into image rows. A selection metric is calculated for each image row and a row to be displayed is selected based on the selection metric. In some embodiments, images representative of a subset of image rows are displayed to a user and responsive to selection of a representative image, the corresponding image row is displayed.

Abstract: Systems and methods are disclosed for selecting target objects within digital images. In particular, in one or more embodiments, the disclosed systems and methods generate a trained neural network based on training digital images and training indicators. Moreover, one or more embodiments of the disclosed systems and methods utilize a trained neural network and iterative user indicators to select targeted objects in digital images. Specifically, the disclosed systems and methods can transform user indicators into distance maps that can be utilized in conjunction with color channels and a trained neural network to identify pixels that reflect the target object.

Abstract: In a measurement device, an image acquisition unit acquires a first image generated by imaging an object to be measured in a first imaging state and acquires one or more second images generated by imaging the object in one or more second imaging states. A specified point setting unit sets a specified point on the first image. A three-dimensional (3D) shape restoration unit restores a 3D shape of the object by using a plurality of images including the second image determined to include a point corresponding to the specified point. A reference dimension setting unit sets a reference dimension on the first image or the 3D shape. A measurement unit measures the object on the basis of the 3D shape, the specified point, and the reference dimension.