Abstract: A liveness detection method includes: controlling a display screen to display a color according to a predetermined color display sequence, the color display sequence including at least two different colors; capturing an image of a target object in a color display process of the display screen; acquiring a color change sequence of a face of the target object in the image over time; and determining whether the target object is live based on a matching relationship between the color display sequence and the color change sequence.

Abstract: A method for facial analytics includes capturing a series of images of individuals from a camera into a circular buffer and selecting a plurality of images from the buffer for analysis in response to a trigger event, wherein the plurality of images are chronologically proximate before and/or after the trigger event in time. The method includes analyzing the plurality of images to determine image quality and selecting one of the plurality of images based on image quality to form a cropped facial image most likely to result in positive facial recognition matching. Methods of signaling to control the pedestrian traffic flow can maximize the individuals' facial alignment to the capturing camera's field of view. Non-relevant facial images associated with individuals outside a given region of interest can be discarded. Facial recognition is run on the resultant cropped facial image. Output can be displayed with information from the facial recognition.

Abstract: This disclosure presents systems and methods to facilitate interaction by one or more participants with content presented across multiple distinct physical locations. A current distinct physical location of a participant may be determined. In response to determining the current distinct physical location in which the participant is located, operation of one or more content devices physically present in the current distinct physical location may be effectuated.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for classifying videos using neural networks. One of the methods includes obtaining a temporal sequence of video frames, wherein the temporal sequence comprises a respective video frame from a particular video at each of a plurality time steps; for each time step of the plurality of time steps: processing the video frame at the time step using a convolutional neural network to generate features of the video frame; and processing the features of the video frame using an LSTM neural network to generate a set of label scores for the time step and classifying the video as relating to one or more of the topics represented by labels in the set of labels from the label scores for each of the plurality of time steps.

Abstract: Techniques and systems are provided for determining features for one or more objects in one or more video frames. For example, an image of an object, such as a face, can be received, and features of the object in the image can be identified. A size of the object can be determined based on the image, for example based on inter-eye distance of a face. Based on the size, either a high-resolution set of features or a low-resolution set of features is selected to compare to the features of the object. The object can be identified by matching the features of the object to matching features from the selected set of features.

Abstract: A method includes activating a first object detector and a second object detector. The first object detector is operable to detect a first type of object in a set of image frames, and the second object detector is operable to detect a second type of object in the set of image frames. The method also includes activating a first set of attribute classifiers and a second set of attribute classifiers. The method also includes generating first statistics for the first object detector and second statistics for the second object detector. The method also includes modifying activation of at least the second set of attribute classifiers based on a comparison of the first statistics and the second statistics.

Abstract: A system that includes computer executable instructions that, when executed by the processor, cause the processor to perform operations including receiving a first 2D map of a location. The first 2D map was generated at a first time based on first scan data from a coordinate measurement scanner and a portable computing device. The coordinate measurement scanner includes a light source, a first image sensor, and a controller. The portable computing device includes a second image sensor. A second 2D map of the location is received. The second 2D map was generated at a second time based on second scan data from the coordinate measurement scanner and the portable computing device. The first 2D map is aligned with the second 2D map, and their contents are compared. Any differences in the contents of the first 2D map and the second 2D map are output.

Abstract: Embodiments described herein provide a method for obtaining information on product inventory and placement in a retail setting. An image including unannotated image data indicative of the retail setting is received. One or more shelves in the retail setting are determined from the unannotated image data, and the image is segmented into one or more sub-images corresponding to the one or more detected shelves. For each sub-image corresponding to a respective detected shelf, a product name is then and a number of appearances of the product name are detected using text recognition on the respective sub-image. Product inventory information and first placement information are derived based at least in part on the detected number of appearances and a shelf level corresponding to the sub-image.

Abstract: The present disclosure relates to a system and a method for estimating an acute cerebral infarction onset time. The method according to the present disclosure includes at least: receiving a first image and a second image of a first patient whose acute cerebral infarction onset time is not identified; extracting an infarction area image from the second image; aligning the second image with the first image; defining an infarction area in the first image, based on a result of the alignment of the second image with the first image; extracting feature information of the first patient, from the infarction area in the first image; comparing the extracted feature information with reference data; and calculating an amount of time that has elapsed since the acute cerebral infarction onset time, based on a result of the comparison of the extracted feature information with reference data.

Abstract: A user identity determining method includes: acquiring target multidimensional feature information of a target user, wherein the target multidimensional feature information includes at least two types of feature information in at least one of biometric feature information or non-biometric feature information; comparing the target multidimensional feature information with multidimensional feature information of a plurality of designated users, respectively, to obtain a comparison result; and determining an identity of the target user based on the comparison result.

Abstract: A computer-implemented method for real time video processing for changing a color of an object in a video, the method being performed in connection with a computerized system comprising a processing unit and a memory, the method comprising: providing an object in the video that at least partially and at least occasionally is presented in frames of the video; detecting the object in the video, wherein said detection comprises detecting feature reference points of the object; tracking the detected object in the video, wherein the tracking comprises creating a mesh that is based on the detected feature reference points of the object and aligning the mesh to the object in each frame; generating a set of node points on the created mesh based on a request for changing color, the set of node points defining an area the color of which is to be changed; and transforming the frames of the video in such way that the object's color is changed within the defined area when the object is presented in frames of the video.

Abstract: A method for guiding resection of local tissue from a patient includes generating at least one image of the patient, automatically determining a plurality of surgical guidance cues indicating three-dimensional spatial properties associated with the local tissue, and generating a visualization of the surgical guidance cues relative to the surface. A system for generating surgical guidance cues for resection of a local tissue from a patient includes a location module for processing at least one image of the patient to determine three-dimensional spatial properties of the local tissue, and a surgical cue generator for generating the surgical guidance cues based upon the three-dimensional spatial properties. A patient-specific locator form for guiding resection of local tissue from a patient includes a locator form surface matching surface of the patient, and a plurality of features indicating a plurality of surgical guidance cues, respectively.

Abstract: In order to select a suitable background image for an image subjected to privacy protection, an image processing apparatus acquires a captured image, and extracts a subject region corresponding to a predetermined subject from the captured image. The image processing apparatus selects a background image to be used for processing from a plurality of background images, based on the captured image, and performing processing for abstracting the extracted subject region for the selected background image.

Abstract: Methods and apparatuses are described for automatic classification of error conditions in automated user interface testing. A server receives an image file corresponding to a current user interface (UI) view of a software application under test. The server analyzes the image file to identify error conditions that exist in the current UI view. The server assigns a classification to the image file according to one or more error types based upon the error conditions identified in the current UI view. The server transmits a notification message to one or more remote computing devices, the notification message comprising the image file and the classification assigned to the image file.

Abstract: A semiconductor die is inspected using an optical microscope to generate a test image of the semiconductor die. A difference image between the test image of the semiconductor die and a reference image is derived. For each defect of a plurality of defects for the semiconductor die, a point-spread function is fit to the defect as indicated in the difference image and one or more dimensions of the fitted point-spread function are determined. Potential defects of interest in the plurality of defects are distinguished from nuisance defects, based at least in part on the one or more dimensions of the fitted point-spread function for respective defects of the plurality of defects.

Abstract: Techniques and systems are provided for segmenting one or more frames. For example, image segmentation can be performed on a first frame of a plurality of frames. The image segmentation results in generation of a segmentation mask. Pixels of the first frame can be modified using the segmentation mask. An amount of movement of one or more pixels of a second frame can be determined. The amount of movement can be determined based on one or more motion characteristics of the second frame. It can be determined whether to perform image segmentation using the second frame or a third frame of the plurality of frames based on the amount of movement of the one or more pixels of the second frame.

Abstract: A machine system includes an image processor to transform a raw digital image to a set of drawing objects comprising individual lines, shapes, and text; a block diagram generator to transform the set of drawing objects into a block diagram; and a flow chart generator to transform the set of drawing objects into a flow chart. A client device receives a raw image signal of a print or display graph from a camera and in response processes the raw image to reduce noise, normalize the raw image data, and reduce pixel information. A server system receives the processed image from the client device and in response operates image processor logic to transform the processed image into a format in which image lines and other geometric objects are manipulatable.

Abstract: A method of providing a semiconductor device and a computer-readable medium having instructions for performing the method are disclosed. The method includes receiving a first wafer defect map that defines comparison regions and identifies visual defect locations for a wafer. A format of the comparison regions is determined, with the format chosen from a group including die-to-die, partial-shot-to-partial-shot and full-shot-to-full-shot. If the comparison format is not die-to-die, mapping information is received that provides die locations within the comparison regions. A wafer layout map is provided that identifies die locations within the wafer.

Abstract: To allow the needed versatile image or video combination now that HDR videos of considerably different luminance characteristics are appearing, the apparatus (301) for combining two images or two videos of images (Im_HDR, Im_LDR), one of them being a high dynamic range image or video, the apparatus comprising: —a dynamic range establishing unit (302) arranged to establish a combination luminance dynamic range (CombRng), being characterized by at least a maximum luminance (LMC) which is determined based on at least one of: a maximum luminance of at least one of the two images or the two videos of images, and a peak brightness of a display for rendering the two images or the two videos of images, the dynamic range establishing unit further comprising a luminance anchor determining unit (303), arranged to determine an anchor luminance (anc) in the combination luminance dynamic range (CombRng), —a color transformation unit (310), arranged to perform at least a luminance transformation on at least one of the two i

Abstract: Techniques for providing improved optical character recognition (OCR) for receipts are discussed herein. Some embodiments may provide for a system including one or more servers configured to perform receipt image cleanup, logo identification, and text extraction. The image cleanup may include transforming image data of the receipt by using image parameters values that optimize the logo identification, and performing logo identification using a comparison of the image data with training logos associated with merchants. When a merchant is identified, a second image clean up may be performed by using image parameter values optimized for text extraction. A receipt structure may be used to categorize the extracted text. Improved OCR accuracy is also achieved by applying on format rules of the receipt structure to the extracted text.