Abstract: Methods, systems, and computer readable storage media for using image processing to develop a library of facial expressions. The system can receive digital video of at least one speaker, then execute image processing on the video to identify landmarks within facial features of the speaker. The system can also identify vectors based on the landmarks, then assign each vector to an expression, resulting in a plurality of speaker expressions. The system then scores the expressions based on similarity to one another, and creates subsets based on the similarity scores.

Abstract: Provided herein is an apparatus for assessing a color characteristic of a gemstone. The apparatus comprises an optically opaque platform for supporting a sample gemstone to be assessed, a daylight-approximating light source to provide uniform illumination to the gemstone, an image capturing component, and a telecentric lens positioned to provide an image of the illuminated gemstone to the image capturing component. Also provided are methods of color analysis based on images collected using such an apparatus.

Abstract: This invention is related to a method to measure and calculate a point spread function PSF of an image detector system based on the analysis of quantum noise that is present in generic image acquisition data, and that is modulated by the transfer function of the digital imaging system. The method allows the calculation of the sharpness of a system without the need for image phantom recordings.

Abstract: Embodiments of the present disclosure relate to the field of image processing technologies and disclose an image processing method and apparatus, an electronic device, and a computer-readable storage medium. The image processing method includes: when an obtained first image includes a human face, performing a first transformation process on the first image to obtain a second image; determining, based on a first target face key point of the human face in the first image, a target position, in the first image, of a second target face key point of the human face in the second image; performing a first movement process on the second image based on the target position; and generating a target image based on the first image and the second image processed through the first movement process, and displaying the target image.

Abstract: Systems and methods for tone mapping of high dynamic range (HDR) images for high-quality deep learning based processing are disclosed. In one embodiment, a graphics processor includes a media pipeline to generate media requests for processing images and an execution unit to receive media requests from the media pipeline. The execution unit is configured to compute an auto-exposure scale for an image to effectively tone map the image, to scale the image with the computed auto-exposure scale, and to apply a tone mapping operator including a log function to the image and scaling the log function to generate a tone mapped image.

Abstract: Systems, methods, and computer media of processing a video are disclosed. An example method may include: receiving a plurality of video frames of a video; generating a plurality of first input features based on the plurality of video frames; generating a plurality of second input features based on reversing a temporal order of the plurality of first input features; generating a first set of joint attention features based on the plurality of first input features; generating a second set of joint attention features based on the plurality of second input features; and concatenating the first set of joint attention features and the second set of joint attention features to generate a final set of joint attention features.

Abstract: Presented herein are systems and methods that provide for automated analysis of medical images to determine a predicted disease status (e.g., prostate cancer status) and/or a value corresponding to predicted risk of the disease status for a subject. The approaches described herein leverage artificial intelligence (AI) to analyze intensities of voxels in a functional image, such as a PET image, and determine a risk and/or likelihood that a subject's disease, e.g., cancer, is aggressive. The approaches described herein can provide predictions of whether a subject that presents a localized disease has and/or will develop aggressive disease, such as metastatic cancer. These predictions are generated in a fully automated fashion and can be used alone, or in combination with other cancer diagnostic metrics (e.g., to corroborate predictions and assessments or highlight potential errors). As such, they represent a valuable tool in support of improved cancer diagnosis and treatment.

Abstract: Systems and methods for color selection are provided and include a non-transitory computer readable medium storing computer executable instructions that, when executed by a processor, configure the computing device to receive an image and determine a dominant color for the image by dividing the image into pixel groups, analyzing pixels in each of the pixel groups at different sample rates based on how close the pixel group is to the center of the image with pixel groups closer to the center of the image having a higher sample rate, and determining the dominant color for the image based on the analyzed pixels in each of the pixel groups. The instructions further configure the computing device to determine a closest matching paint color for the dominant color for the image and display a color name or a color code associated with the closest matching paint color for the dominant color.

Abstract: A classification training method for training classifiers adapted to identify specific mutations associated with different cancer including identifying driver mutations. First cells from mutation cell lines derived from conditions having the number of driver mutations are acquired and 3D image feature data from the number of first cells is identified. 3D cell imaging data from the number of first cells and from other malignant cells is generated, where cell imaging data includes a number of first individual cell images. A second set of 3D cell imaging data is generated from a set of normal cells where the number of driver mutations are expected to occur, where the second set of cell imaging data includes second individual cell images. Supervised learning is conducted based on cell line status as ground truth to generate a classifier.

Abstract: A production monitoring and analysis method based on an image data algorithm includes: obtaining a reconstructed gray histogram according to a gray image of an image where a product identification code is located; obtaining a segmentation threshold of an Otsu algorithm for segmenting the reconstructed gray histogram, obtaining the adjustment of the gray level in the sub-gray histogram according to the number of pixels corresponding to each gray level in the reconstructed gray histogram and the segmentation threshold, correcting the sub-gray histogram to obtain a corrected sub-gray histogram according to the adjustment of the gray level in the sub-gray histogram, the lateral segmentation threshold of the sub-gray histogram, and all the gray levels greater than the lateral segmentation threshold, and obtaining an enhanced gray image according to the corrected sub-gray histogram. The method avoids the loss of original information when using histogram equalization for image enhancement.

Abstract: An apparatus includes one or more processors that function as an image acquisition unit configured to acquire a training image and a correct answer image, a generation unit configured to input the training image to a neural network to generate an output image, an error acquisition unit configured to subject each of the correct answer image and the output image to processing for adjusting a color signal value, and acquire an error between the correct answer image and the output image that have been subjected to the processing, and an update unit configured to update parameters of the neural network based on the acquired error.

Abstract: An example system includes a landmark engine to detect a facial landmark in an image of a face. The system includes a comparison engine to determine a difference between the facial landmark in the image and a facial landmark of a neutral face. The system also includes an action engine to determine whether a facial action unit occurred based on whether the difference satisfies a condition.

Abstract: A meme generation method, an electronic device, and a storage medium are provided. The method includes: determining a plurality of second expression images corresponding to a target face image based on a plurality of first expression images contained in a first meme; generating a second meme corresponding to the target face image based on the plurality of second expression images corresponding to the target face image; wherein, determining an affine transformation parameter between the target face image and an i-th first expression image in the plurality of first expression images according to a corresponding relation between a face key point in the target face image and a face key point in the i-th first expression image; and transforming the target face image based on the affine transformation parameter to obtain an i-th second expression image corresponding to the target face image.

Abstract: Disclosed are methods, systems, and non-transitory computer-readable medium for color and pattern analysis of images including wearable items. For example, a method may include receiving an image depicting a wearable item, identifying the wearable item within the image by identifying a face of an individual wearing the wearable item or segmenting a foreground silhouette of the wearable item from background image portions of the image, determining a portion of the wearable item identified within the image as being a patch portion representative of the wearable item depicted within the image, deriving one or more patterns of the wearable item based on image analysis of the determined patch portion of the image, deriving one or more colors of the wearable item based on image analysis of the determined patch portion of the image, and transmitting information regarding the derived one or more colors and information regarding the derived one or more patterns.

Abstract: A system is disclosed including at least one memory including computer program instructions, which when executed by at least one processor, cause the system to at least generate, based on a plurality of images from a camera, a first map including a first plurality of features; generate, based on data from a light ranging sensor, a second map including a second plurality of features; and determine, based on a comparison of the first plurality of features and the second plurality of features, a position of the first map relative to the second map. A corresponding method and non-transitory computer-readable medium are also provided.

Abstract: Disclosed is a compound expression recognition method with few samples of multi-domain adversarial learning. To extract compound expression features with diversity and complexity with few samples, multiple small sample datasets are fused, and divided into expression sub-domains, and multi-domain adversarial learning is performed to improve the performance of compound expression recognition. Based on the generative adversarial network framework, the face domain and the contour-independent compound expression domain are fused in the generative network to enhance diversity and complexity, and two discriminators are designed to guide the generator. The face discriminator uses the face domain to guide the generator and identify the generator to generate expression-independent face identity attributes, so that the generator has identity diversity.

Abstract: This disclosure discloses a resident area prediction method, apparatus, device and storage medium, involving artificial intelligence technology, big data, deep learning and multi-task learning. The specific implementation plan is: acquiring a resident area data of a target user, and the resident area data including the resident area of the target user and the corresponding resident time; obtaining an association relationship between the resident areas of the target user by inputting the resident area data into an area relationship model, and the area relationship model is used to reflect a position relationship between the areas; determining a time-sequence relationship between the areas visited by the target user, according to the association relationship, the resident time and the visiting POI data; predicting a target resident area of the target user, according to the time-sequence relationship and the basic attribute information of the target user.

Abstract: Systems, devices and methods operative for identifying a reference within a figure and an identifier in a text associated with the figure, the reference referring to an element depicted in the figure, the reference corresponding to the identifier, the identifier identifying the element in the text, placing the identifier on the figure at a distance from the reference, the identifier visually associated with the reference upon the placing, the placing of the identifier on the figure is irrespective of the distance between the identifier and the reference.

Abstract: In one embodiment, a method includes receiving an input video comprising a plurality of image frames including an object of interest. Based on the plurality of image frames, a motion associated with the object of interest is determined, and the plurality of image frames are classified using a machine-learning model to identify one of the plurality of image frames that indicates detection of the determined motion.

Abstract: Disclosed is an intelligent micromanipulation system based on machine vision, including a base, wherein a microscope, a rotating table and two lifting tables are arranged on the base, the microscope is located right above the rotating table, the two lifting tables are arranged at two sides of the rotating table, respectively, and each is provided with a mechanical arm, each of the two manipulators is provided with an end effector, the mechanical arm is capable of driving the corresponding end effector to perform fine adjustment in x, y and z directions, one of the end effectors clamps a suction holding needle in communication with a suction pump, while the other end effector clamps an injection needle in communication with an injection pump; and the rotating table includes a tray, a rotating mechanism and a driving device, and the driving device drives the tray to rotate via the rotating mechanism.