Abstract: A virtual window configuration method includes the following steps. A processor generates a virtual window. A depth detection sensor generates depth information based on an image. The processor analyzes the depth information to generate a depth matrix. The processor finds a depth configuration block in the image using the depth matrix. A feature point detection sensor generates feature point information for the image. The processor analyzes the feature point information to generate a feature point matrix. The processor finds a feature point configuration block in the image using the feature point matrix. The processor moves the virtual window to the depth configuration block or the feature point configuration block.

Abstract: Disclosed herein are methods, systems, and computer-readable storage media for generating three-dimensional (3D) images of a scene. According to an aspect, a method includes capturing a real-time image and a first still image of a scene. Further, the method includes displaying the real-time image of the scene on a display. The method also includes determining one or more properties of the captured images. The method also includes calculating an offset in a real-time display of the scene to indicate a target camera positional offset with respect to the first still image. Further, the method includes determining that a capture device is in a position of the target camera positional offset. The method also includes capturing a second still image. Further, the method includes correcting the captured first and second still images. The method also includes generating the three-dimensional image based on the corrected first and second still images.

Abstract: A front-end image acquisition component acquires photographs and/or videos of the exterior of a vehicle traveling on a path between a first predefined location and a second predefined location. In one aspect, an image acquisition system comprises a first camera support structure, a second camera support structure, an image processor, and a memory. Cameras are affixed to each of the camera support structures for acquiring image data of a subject vehicle. Image data is controlled by the image processor and the memory. In another aspect, an image acquisition system comprises a first camera tower, a second camera tower, a camera boom. Cameras are affixed to each of the camera towers.

Abstract: System and method for detecting the authenticity of products by detecting a unique chaotic signature. Photos of the products are taken at the plant and stored in a database/server. The server processes the images to detect for each authentic product a unique authentic signature which is the result of a manufacturing process, a process of nature etc. To detect whether the product is genuine or not at the store, the user/buyer may take a picture of the product and send it to the server (e.g. using an app installed on a portable device or the like). Upon receipt of the photo, the server may process the receive image in search for a pre-detected and/or pre-stored chaotic signature associated with an authentic product. The server may return a response to the user indicating the result of the search. A feedback mechanism may be included to guide the user to take a picture at a specific location of the product where the chaotic signature may exist.

Abstract: In one implementation, a computing device to provide a graphical user interface (GUI) for presenting content includes one or more processors; a network interface to establish a network connection with a remote server system; a display to output a plurality of graphical elements as part of the GUI; one or more input devices to receive user input related to the plurality of graphical elements; and memory storing instructions that, when executed, cause the one or more processors to perform operations including selecting a first content element; selecting second content elements; detecting a third content element comprising a content summary of the second content elements; and outputting, in the GUI on the display, a first graphical element for the first content element and a third graphical element for the third content element, wherein second graphical elements for the second content elements are hidden or collapsed in the GUI.

Abstract: A fingerprint processing device includes a match processing unit configured to determine, based on a first degree, a plurality of feature points having a large value of the first degree among the feature points of a fingerprint specified in a fingerprint image of a matching source, the first degree representing a first distance to other feature points, as representative feature points used in match processing of the fingerprint.

Abstract: A face authentication apparatus includes a face image acquisition unit that acquires a face image of an authentication target, a collation unit that performs face authentication by calculating similarity between face information of the face image of the authentication target and reference face image of each registered user and comparing the similarity with a threshold, a prediction unit that predicts a change in the similarity on the basis of similarity history on authentication success, and a threshold change unit that changes the threshold on the basis of the prediction result.

Abstract: An in-vehicle monitoring device includes a first imaging member, a second imaging member, and a controller. The first imaging member is configured to perform first imaging to capture a first image of one or more occupants in a passenger compartment of the vehicle. The second imaging member is configured to capture a second image of the one or more occupants. The controller is configured to execute a monitoring process on the first image and the second image. The first imaging member and the second imaging member are disposed in a center portion of the vehicle in a vehicle width direction of the vehicle so as to be arranged side-by-side in the vehicle width direction such that at least a portion of an imaging range of the first imaging member and at least a portion of an imaging range of the second imaging member overlap.

Abstract: Example systems, devices, media, and methods are described for controlling the presentation of a series of virtual or graphical elements on a display in response to hand gestures detected by an eyewear device that is capturing frames of video data with its camera system. An image processing system detects a series of hand shapes in the video data and determines whether it matches a predefined hand gesture. Each predefined hand gesture is associated with an action; for example, a leafing gesture is associated with a scrolling action. The system controls the display of a series of virtual elements, in accordance with the associated action. In an example series of hand shapes that includes flexing and extending the fingers of a single hand severally and continually in a leafing motion, the matching predefined leafing gesture is associated with a scrolling action, which displays the series of items in a display order, sequentially and in accordance with the detected speed of the moving fingers.

Abstract: A method of evaluating a patterning process, the method including: obtaining the result of a first measurement of a first metrology target; obtaining the result of a second measurement of a second metrology target, the second metrology target having a structural difference from the first metrology target that generates a sensitivity difference and/or an offset, of a process parameter of the patterning process between the first and second metrology targets; and determining a value pertaining to the patterning process based on the results of the first and second measurements.

Abstract: Disclosed are methods, apparatus and systems for gesture recognition based on neural network processing. One exemplary method for identifying a gesture communicated by a subject includes receiving a plurality of images associated with the gesture, providing the plurality of images to a first 3-dimensional convolutional neural network (3D CNN) and a second 3D CNN, where the first 3D CNN is operable to produce motion information, where the second 3D CNN is operable to produce pose and color information, and where the first 3D CNN is operable to implement an optical flow algorithm to detect the gesture, fusing the motion information and the pose and color information to produce an identification of the gesture, and determining whether the identification corresponds to a singular gesture across the plurality of images using a recurrent neural network that comprises one or more long short-term memory units.

Abstract: A method includes identifying, within an image that represents a fingerprint, a plurality of keypoints. The method also includes determining a plurality of pixel vectors by transforming, for each respective keypoint, a corresponding two-dimensional (2D) array of pixel values associated with the respective keypoint into a corresponding pixel vector, and obtaining a plurality of filter vectors that represent, for each respective filter of a plurality of filters, a transformation of a corresponding 2D array of filter values of the respective filter into a corresponding filter vector. The method additionally includes convolving the plurality of keypoints with the plurality of filters by multiplying, using a tensor processing hardware, a pixel matrix formed by the plurality of pixel vectors and a filter matrix formed by the plurality of filter vectors, and determining, based on the convolving, a representation of the fingerprint.

Abstract: An eye reconstruction-based eye tracking method and apparatus are provided. The eye tracking method includes generating a reconstructed image by performing eye reconstruction with respect to an input image, determining a difference value between the input image and the reconstructed image, selecting one of the input image, the reconstructed image, and a replacement image as a target image based on the determined difference value, and performing eye tracking based on the target image.

Abstract: A plurality of pixel-based sampling points are identified within an image, wherein sampling points of a pixel are distributed within the pixel. For individual sampling points of individual pixels, a corresponding radiance vector is estimated. A radiance vector includes one or more radiance values characterizing light received at a sampling point. A first machine learning module generates, for each pixel, a corresponding intermediate radiance feature vector, based on the radiance vectors associated with the sampling points within that pixel. A second machine learning module generates, for each pixel, a corresponding final radiance feature vector, based on an intermediate radiance feature vector for that pixel, and one or more other intermediate radiance feature vectors for one or more other pixels neighboring that pixel. One or more kernels are generated, based on the final radiance feature vectors, and applied to corresponding pixels of the image, to generate a lower noise image.

Abstract: User interaction concepts, principles and algorithms for gestures involving facial expressions, motion or orientation of body parts, eye gaze, tightening muscles, mental activity, and other user actions are disclosed. User interaction concepts, principles and algorithms for enabling hands-free and voice-free interaction with electronic devices are disclosed. Apparatuses, systems, computer implementable methods, and non-transient computer storage media storing instructions, implementing the disclosed concepts, principles and algorithms are disclosed. Gestures for systems using eye gaze and head tracking that can be used with augmented, mixed or virtual reality, mobile or desktop computing are disclosed. Use of periods of limited activity and consecutive user actions in orthogonal axes is disclosed. Generation of command signals based on start and end triggers is disclosed. Methods for coarse as well as fine modification of objects are disclosed.

Abstract: The present disclosure describes techniques for creating videos using virtual characters. Creation of a video may be initiated by a user. Camera input comprising a human body of the user may be received. The camera input may be split into a first stream for removing the human body and a second stream for animating a virtual character in the video. An inpainting filter may be applied to remove the human body in real time from the camera input. The inpainting filter may be configured to accelerate texture sampling. Output of the inpainting filter may be blended with images comprised in the camera input to generate camera input backgrounds.

Abstract: Systems, apparatuses, and methods for implementing a safety monitor framework for a safety-critical computer vision (CV) application are disclosed. A system includes a safety-critical CV application, a safety monitor, and a CV accelerator engine. The safety monitor receives an input image, test data, and a CV graph from the safety-critical CV application. The safety monitor generates a modified image by adding additional objects outside of the input image. The safety monitor provides the modified image and CV graph to the CV accelerator which processes the modified image and provides outputs to the safety monitor. The safety monitor determines the likelihood of erroneous processing of the original input image by comparing the outputs for the additional objects with a known good result. The safety monitor complements the overall fault coverage of the CV accelerator engine and covers faults only observable at the level of the CV graph.

Abstract: An exemplary method includes a gesture recognition system determining, based on imagery of a user while the user touchlessly interacts with a user interface of a computer system, a configuration of a plurality of landmarks associated with the user and comparing the configuration of the plurality of landmarks to defined landmark configurations associated with a plurality of defined gestures. Each of the plurality of defined gestures may be associated with a different user input enterable by way of the user interface of the computer system. The method may further include the gesture recognition system selecting, based on the comparing of the configuration of the plurality of landmarks to the defined landmark configurations associated with the plurality of defined gestures, a defined gesture included in the plurality of defined gestures, and directing the computer system to enter a user input that is associated with the defined gesture.

Abstract: Systems and methods for analyzing trends in image data is disclosed. A trend query is received relating to an object category and defining two or more groups of interest for which trend data is to be determined with a defined time period. Visual tokens of interest are identified relating to the object category for use in searching a token database. One or more image data sets are identified that are associated with each of the two or more groups of interest. Visual tokens are analyzed matching the visual tokens of interest that are associated with the identified image data sets to generate trend data for each of the two or more groups of interest for the defined period of time. An output is generated based on a comparison of the trend data generated for the two or more groups of interest for the defined period of time.

Abstract: A target tracking method is provided for a computer device. The method includes determining a target candidate region of a current image frame; capturing a target candidate image matching the target candidate region from the current image frame; determining a target region of the current image frame according to an image feature of the target candidate image; determining motion prediction data of a next image frame relative to the current image frame by using a motion prediction model and according to the image feature of the target candidate image; and determining a target candidate region of the next image frame according to the target region and the motion prediction data.

Abstract: A single-instruction, multiple data processor performs object detection in an image by testing for a plurality of object features in a plurality of image regions, the processor comprising: a set of computation units operable to execute a plurality of classifier sequences in parallel, each classifier sequence comprising a plurality of classifier routines, and each classifier routine comprising identical instructions to the other classifier routines in each of the plurality of classifier sequences; wherein each computation unit is configured to independently maintain data identifying an image region and a feature under test on that computation unit, and each classifier routine is arranged to access the data, test the identified feature against the identified image region and update the data such that the computation units are operable to concurrently test different features against different image regions.

Abstract: A front-end image acquisition component acquires photographs and/or videos of the exterior of a vehicle traveling on a path between a first predefined location and a second predefined location. In one aspect, an image acquisition system comprises a first camera support structure, a second camera support structure, an image processor, and a memory. Cameras are affixed to each of the camera support structures for acquiring image data of a subject vehicle. Image data is controlled by the image processor and the memory. In another aspect, an image acquisition system comprises a first camera tower, a second camera tower, a camera boom. Cameras are affixed to each of the camera towers.

Abstract: This electronic endoscope system includes an evaluation value calculation unit, an assessment unit, and a representative value determination unit. The evaluation value calculation unit is configured so as to obtain an evaluation value indicating an extent of a lesion in biological tissue in each of a plurality of images captured in a predetermined section along the depth direction of a region in an organ. The assessment unit is configured so as to assess whether the extent of the lesion in the section is changed on the basis of the degree of variation of the evaluation value. The representative value determination unit is configured so as to define a representative value of the section representing the evaluation value, in a different method when the extent of the lesion is assessed to be changed and when the extent of the lesion is assessed not to be changed.

Abstract: A method for detection and pathological classification of polyps via colonoscopy based on an anchor-free technique includes: performing feature extraction on a color endoscopic image that is pretreated, enhancing and extending the extracted features, decoding the feature information of the enhanced feature and the extended feature through an anchor-free detection algorithm to acquire a polyp prediction box and a prospect prediction mask, then respectively extracting global and local feature vectors from the extended feature and the prospect prediction mask, and combining the global feature vector with the local feature vector, so as to predict the type of polyps through a full-connection layer. Through the present application, the type of polyps can be correctly predicted, and the detection rate of polyps and the accuracy rate of pathological classification are improved.

Abstract: Apparatus and methods for determining information about one or more objects in a 3-dimensional (3D) space are disclosed. One aspect of the method includes defining a virtual ground plane within a monitored 3D space. The virtual ground plane is divided into a plurality of bins. Each bin has corresponding counter value. An object is detected in a respective image captured by each of a plurality of sensors. A respective line segment is selected corresponding to a respective light between each of the plurality of image sensors and the detected object. One or more bins of the virtual ground plane are selected onto which a respective projected line segment of each respective line segment overlap. Each counter value for each of the one or more selected bins is increased. A location of the object is determined based on a bin of the one or more bins having a highest counter value.

Abstract: A parallel presentation system includes computer hardware including a parallel presentation platform (PPP) connected to an extended reality (XR) system associated with a user. The computer hardware is configured to perform the following operations. A lookup point associated with the user is identified by the PPP. The PPP determines that the user has shifted focus from a first data stream to a second data stream. A shift time associated with the shift along with an identification of the first data stream is stored by the PPP in association with the user. A summarization of the first data stream is generated using a summarization engine of the PPP and the summarization is based upon the shift time and the lookup point. The summarization is forwarded by the PPP to the XR system. Information regarding the summarization is configured to be parallel-presented by the XR system associated with the user.

Abstract: A feature point detection apparatus for detecting feature points in image data includes an image data providing unit for providing the image data, a key point determination unit for determining key points in the image data, a feature determination unit for determining features associated with the key points, each describing a local environment of a key point in the image data, and a feature point providing unit for providing the feature points. A feature point is represented by the position of a key point in the image data and the associated features. The image data comprise intensity data and associated depth data, and the determination of the key points and the associated features is based on a local analysis of the image data in dependence on both the intensity data and the depth data.

Abstract: Technologies for summarizing tax documents that include an unstructured portion, such as K1 filings. The system extracts data from both the structured information, such as a K1 facepage, and unstructured information, such as whitepaper statement(s). The system includes machine learning model(s) to determine the information to be extracted from the unstructured information. The machine learning model(s) generate a confidence level associated with the extracted unstructured information that represents a prediction on how likely the extracted unstructured information was accurately extracted. The system generates a document in an electronic interchange format that represents both the structured and unstructured information in the analyzed tax document.

Abstract: A method for building a robust classifier against evasion attacks includes receiving an application, identifying one or more features of the application, and determining a first confidence score for a first version of the application including a first set of features and determining a second confidence score for a second version of the application including a second set of features, the first set of features is different than the second set of features. The method also includes determining a difference between the first confidence score and the second confidence score, and comparing the difference with a convergence threshold. The method includes, based on the comparison, determining whether the first confidence score exceeds a confidence score threshold, and generating a report based on determining the first confidence score exceeds the confidence score threshold.

Abstract: Technology described herein includes a method that includes obtaining an image of a fluid of a microfluidic analysis system. The microfluidic analysis system includes or receives a container that contains the fluid for measurement of analyte or quality determination. A region of interest (ROI) is identified based on the image. The ROI is a set of pixel values for use in the measurement of the analyte or the quality determination of the fluid, fluidic path, or measuring system. Identifying the ROI includes: determining an alignment of the container of the fluid with the imaging device based on the image, and identifying the ROI based on information about the measurement of the fluid or based on information about non-analyte features of the fluid. An analysis of the image of the fluid is performed using the set of pixel values of the ROI.

Abstract: The described implementations enable a seller to sell items through multiple e-commerce channels without having to maintain independent merchant accounts at each channel. For example, a seller may sell items directly and through a management service. When a user request to purchase an item from the seller through the management service is received, the management service sends the purchase information to the seller so that the seller can complete the purchase as if the purchase were being made directly with the seller. Upon completion of the purchase, the seller provides a confirmation back to the management service and provides the item directly to the user.

Abstract: A distributed data integration device includes an acquisition unit configured to acquire, for a piece of analysis target data, an anchor data intermediate representation and an analysis target intermediate representation, the anchor data intermediate representation being an intermediate representation obtained by converting anchor data by a first function, the anchor data being data commonly used in integration of a plurality of the pieces of analysis target data that are distributed, the analysis target intermediate representation being an intermediate representation obtained by converting the analysis target data by the first function, an anchor data conversion unit configured to convert, for the piece of analysis target data, a plurality of the anchor data intermediate representations by a second function, a calculation unit configured to calculate, for the piece of analysis target data, the second function that minimizes a difference between the plurality of the anchor data intermediate representations, a

Abstract: An image inspection apparatus includes a designated area acquisition device that acquires information related to an area designated in a recording medium, wherein when trial printing is instructed, a read image of an image printed on the recording medium in the trial printing and an image of the area generated on the basis of the information related to the area acquired by the designated area acquisition device are combined.

Abstract: An abnormality detection apparatus is provided. The abnormality detection apparatus includes a first generation part configured to generate pseudo-abnormal image data by synthesizing a substantially circular image at a random position of an image of normal image data obtained by photographing equipment that includes a liquid supply and supplies a liquid from the liquid supply without an abnormality, a second generation part configured to generate a determination model for determining whether the equipment is normal or abnormal by performing learning of the normal image data and the pseudo-abnormal image data, an acquisition part configured to acquire image data obtained by photographing the equipment, and a detection part configured detect an abnormality in the equipment from the image data acquired by the acquisition part using the determination model.

Abstract: Systems and methods for image-based item identification are disclosed. Image data corresponding to one or more images depicting an item may be sent to one or more remote systems for image-based item identification. The identification indications and/or identification confidence scores received from the remote systems may be aggregated and weighted based at least in part on one or more factors related to the remote systems, the results, domains, image capture timing, image capture angles, and/or events to more accurately identify an item depicted in the images.

Abstract: In some aspects, the disclosure is directed to methods and systems for automatic context-based annotation by leveraging a priori knowledge from annotations in template documents. A large library of template documents may be generated and pre-processed in many implementations to identify annotations or other inclusions commonly present on documents related to or conforming to the template. Newly scanned documents may be compared to these templates, and when a similar template is identified, annotation locations and types from the template may be applied to the newly scanned document to recognize and classify annotations and inclusions. To increase efficiency and provide scalability, comparisons of scanned documents and template documents may be distributed amongst a plurality of computing devices for processing in parallel, with similarity results aggregated.

Abstract: A computer implemented method transforms data. Responsive to receiving a data transformation of an input string to an output string, a computer system identifies mappable tokens in the input string that are mappable to the output string. The computer system creates a set of initial mappings for a set of common tokens in the mappable tokens. The set of initial mappings maps the set of common tokens from the input string to the output string. The computer system creates a set of user mappings that maps the mappable tokens from input string to the output string using a user input to the set of initial mappings. The computer system generates program code that transform input strings to output strings using the set of user mappings that maps the mappable tokens from input string to the output string, wherein the program code is used to transform input strings to output strings.

Abstract: A display control device includes a first display control unit performing control so as to display a page, which is being displayed in a real space, in a first material as a presentation material used in a presentation by a presenter in a first position in a virtual reality space, a second display control unit performing control so as to display a second material in a second position which is different from the first position in the virtual reality space, and an operation input information acquisition unit acquiring first operation input information as operation input information which is input by a viewer experiencing the virtual reality space and which is about display of the second material, in which the second display control unit changes a display manner of the second material based on the first operation input information.

Abstract: In an integrated circuit (IC) assessment method, an artificial intelligence (AI) component comprising at least one artificial neural network (ANN) is trained to transform layout rendering tiles of a rendering of a reference IC into corresponding reference layout image tiles extracted from at least one layout image of the reference IC. Using the trained AI component, standard cell layout renderings of a library of GDSII or OASIS standard cell layout renderings are transformed into as-fabricated standard cell layout renderings forming a library of as fabricated standard cell layout renderings. Instantiated standard cells and their placements in the layout image of an IC-under-test are identified by matching the instantiated standard cells with corresponding as-fabricated standard cell layout renderings retrieved from the library of as fabricated standard cell layout renderings.

Abstract: A method and computing system for performing the method are presented. The method may include receiving image information representing an object; identifying a set of one or more matching object recognition templates associated with a set of one or more detection hypotheses. The method may further include selecting a primary detection hypothesis associated with a matching object recognition template; generating a primary candidate region based on the matching object recognition template; determining at least one of: (i) whether the set of one or more matching object recognition templates has a subset of one or more remaining matching templates, or (ii) whether the image information has a portion representing an unmatched region; and generating a safety volume list based on at least one of: (i) the unmatched region, or (ii) one or more additional candidate regions that are generated based on the subset of one or more remaining matching templates.

Abstract: Video encoders and video decoders are configured to supplemental enhancement information (SEI) messages. The SEI messages may include picture orientation transform type syntax elements that indicate how a picture may be rotated and/or mirrored. The SEI messages may also include quality metrics.

Abstract: In some aspects, systems and methods for efficiently clustering a large-scale dataset for improving the construction and training of machine-learning models, such as neural network models, are provided. A dataset used for training a neural network model configured can be clustered into a first set of clusters and a second set of clusters. The neural network model can be constructed with a number of nodes in a hidden layer that is based on the number of clusters in the first set of clusters. The neural network can be trained based on training samples selected from the second set of clusters. In some aspects, the trained neural network model can be utilized to satisfy risk assessment queries to compute output risk indicators for target entities. The output risk indicator can be used to control access to one or more interactive computing environments by the target entities.

Abstract: A method of machining a surface of a component. The method comprises scanning the surface of the component to obtain scanned electronic 3D data representing the scanned surface of the component locating a surface defect of the scanned surface and identifying a defect region that surrounds and includes the surface defect, and providing electronic 3D data representing a patch having the desired shape of the defect region. The method also comprises transforming the patch to generate a tooling path for repairing the surface defect. The transformation comprising translating a plurality of nodes of the patch. The translation distance of each node based on the distance of that node from an origin node of the patch. The method further comprises machining the surface of the component according to the generated tooling path.

Abstract: This application relates to a tissue nodule detection and tissue nodule detection model training method, apparatus, device, storage medium and system.

Abstract: Systems and methods are provided for utilizing histogram views for improved visualization of three-dimensional (3D) medical images. Imaging data obtained during medical imaging examination of a patient may be processed, with the imaging data corresponding to a particular medical imaging technique. At least one medical image may be generated based on processing of the imaging data. Histogram data may be generated based on the at least one medical image. At least one histogram may be displayed along with the at least one medical image or a projection of the at least one medical image, with the at least one histogram including or being is based on the histogram data, and with the at least one histogram being displayed next to and aligned with the at least one medical image or the projection of the at least one medical image.

Abstract: Techniques related to embedding a 3D object model within a 3D scene are discussed. Such techniques include determining two or more object mask images for two or more corresponding cameras trained on the 3D scene, projecting 3D points from the 3D object model to the image planes of the two or more cameras, and determining a position and orientation of the 3D object model in the scene using the object mask images and the projected 3D points.

Abstract: Methods and systems for controlling navigation of an autonomous vehicle for traversing a drivable area are disclosed. The methods include receiving information relating to a drivable area that includes a plurality of polygons, identifying a plurality of logical edges that form a boundary of the drivable area, sequentially and repeatedly analyzing concavities of each the plurality of logical edges until identification of a first logical edge that has a concavity greater than a threshold, creating a first logical segment of the boundary of the drivable area. This segmentation may be repeated until each of the plurality of logical edges has been classified. The method may include creating and adding (to a map) a data representation of the drivable area that comprises an indication of the plurality of logical segments, and adding the data representation to a road network map comprising the drivable area.

Abstract: A document processing apparatus includes a processor configured to extract an image area, in which an image is disposed, from a plurality of documents to be processed, perform an image recognition process on the image area, compare information on the image of the image area for each document, the information being obtained by performing the image recognition process, and decide a difference for the documents based on a result of comparison of the information on the image and a decision rule for the documents.

Abstract: The image recognition method includes: obtaining an image data stream, wherein the image data frame includes a current frame; performing image recognition on an object in the current frame to generate a first box corresponding to the current frame; detecting movement of the object to generate a second box corresponding to the current frame; and determining the object as a tracking target according to the first box and the second box.

Abstract: Techniques for texture-based authentication of digital identity documents are disclosed. The disclosed techniques include authentication based on global texture information and/or on local texture information. Global texture-based authentication may include generating a global texture profile for an identity document image and comparing the global texture profile with a stored profile associated with a jurisdiction class of the identity document. Local texture-based authentication may include generating one or more local texture patches representative of texture information of one or more select local blocks of the ID. The one or more local texture patches are provided as input to one or more local detectors each trained to detect the presence of a forgery based on a target manipulation space.