Abstract: According to an embodiment, a computing device includes a processing circuitry. The processing circuitry receives an input of tensor data. The processing circuitry sets a window in the tensor data. The processing circuitry compares, for each pair of coordinates in the tensor data within the window, a pixel value at the pair of coordinates with one or more thresholds, and selects a weight value corresponding to a comparison result. The processing circuitry adds the weight values selected for the respective pairs of coordinates to obtain a cumulative value. The processing circuitry derives a value based at least in part on the cumulative value.

Abstract: A cursor image detection comparison and feedback status determination method is disclosed. The method is based on a non-invasive data-extraction system architecture, and uses an image processing unit to perform detection comparison on a cursor image shown on an operation screen outputted from a machine controller. The method includes steps of obtaining cursor foreground and background images set by a user, and selecting an algorithm to process the cursor foreground and background images to generate a cursor mask, and reading a cursor image and applying the cursor mask on the cursor image for pattern comparison, transmitting information of a comparison result and a cursor feedback status to a software control system, so as to provide a correction system to perform a cursor process program and check whether the movement of the cursor meet a position controlled by a feedback and correction system, thereby completing closed-loop control for the cursor.

Abstract: A system and method for matching a pattern may include generating a set of model descriptors representative of segment features of a first imaged object. A set of query descriptors representative of segment features of a second imaged object may be generated. A first model segment may be selected to align with the query segments to determine if any of the query segments correspond with the first model segment based on respective model descriptors and query descriptors. An hypothesis may be generated by computing a transformation to match the selected first model descriptor with a query descriptor. The hypothesis may be validated by a model fitting algorithm when comparing other transformed model descriptors with other query descriptors. Based on a consensus value from the model fitting algorithm, a determination as to whether a pattern match exists between the first and second images may be made.

Abstract: A lane line tracking method and device are provided. The method can include: projecting a lane line detection result of previous K frames preceding a current frame in a camera coordinate system to a world coordinate system, to obtain a first projection result, wherein K is a positive integer greater than or equal to 1, and the previous K frames are consecutive K frames preceding the current frame; projecting the first projection result of the previous K frames in the world coordinate system to a camera coordinate system of the current frame, to obtain a second projection result; and determining, in the camera coordinate system of the current frame, lane line groups of the current frame, according to lane line groups in the second projection result of the previous K frames.

Abstract: An image processing method to reduce access pressure of each image in an image set, where the image processing method includes obtaining a quantity of times each image layer in an image set is accessed, determining one or more first image layers, where a quantity of times the first image layer in the image set is accessed is greater than a first threshold, and the first image layer has at least two child image layers, generating a copy of the first image layer, and modifying some child image layers of the first image layer to child image layers of the copy of the first image layer.

Abstract: An object identification method includes: establishing a training data base including a photographing distance of a training image and a training camera parameter; in photographing a target test object, obtaining a test image, a depth image, an RGB image and a test camera parameter; and based on the training database, the depth image and the test camera parameter, adjusting the RGB image wherein the adjusted RGB image having a size equivalent to the training image of the training database.

Abstract: The APPARATUSES, METHODS AND SYSTEMS FOR A VIDEO REMOTE DEPOSIT CAPTURE PLATFORM (hereinafter “RDC-Video”) provides a platform for remote deposit by obtaining images of a check from streaming video captured by a video camera, wherein the RDC-Video transforms captured check images and/or entered check deposit information inputs via RDC-Video components into deposit confirmation outputs. For example, in one embodiment, a user may employ a personal computer connected to a web camera, and/or a smartphone with a built-in camera to initiate the remote deposit by holding a check in front of the camera, and the RDC-Video may capture images of the check and send them to a financial institution for deposit processing.

Abstract: An autonomous store that tracks shopper movements and actions, and performs store cleaning actions based on analysis of shopper activity. Cleaning actions may include disinfecting the store or regions within the store using radiation, fogging or spraying, or ventilation. Cleaning actions may be targeted; for example, zones where shoppers linger or congregate may be cleaned more frequently or intensively, or shelves or items that shoppers touch may be cleaned after these interactions. Shopper activity information may be used to limit the number of shoppers in a store at once, for example by denying entry when the store is at capacity. The density of shoppers in regions of the store may be communicated to shoppers so that they can limit their interactions with other shoppers. Shopper activity history may be used for contact tracing by identifying other shoppers that may have been exposed to an individual who was in the store.

Abstract: Embodiments of this disclosure provide a person searching method and apparatus and an image processing device. The method includes: performing person detection on a reference image, determining a query person, and acquiring property information on the query person; performing person detection on at least one video surveillance image, determining all candidate persons, and acquiring property information on all the candidate persons; calculating a match score of each candidate person according to the property information on the query person and property information on each candidate person, and selecting a predetermined number of candidate persons in a descending order of the match scores; and calculating similarities between the query person and the selected candidate persons, and taking a candidate person in the selected candidate persons having a highest similarity with the query person as the query person.

Abstract: A computing system receives historical data. The historical data comprises physical actions taken in an experiment in a physical environment. The experiment comprises user-defined stages. The historical data comprises a recorded outcome, according to user-defined performance indicator(s) related to the user-defined stages, for each physical action taken in the experiment. The system generates, by a discrete event simulator, a computing representation of a simulated environment of the physical environment. The simulated environment comprises processing stages. The system obtains simulation data. The simulation data comprises simulated actions taken by the discrete event simulator. The simulation data comprises a predicted outcome, according to user-defined performance indicator(s) related to the processing stages, for each simulated action taken by the discrete event simulator. The system validates accuracy of the discrete event simulator at predicting the recorded outcome in the experiment.

Abstract: Disclosed are methods, apparatus and systems for real-time gesture recognition. One exemplary method for the real-time identification of a gesture communicated by a subject includes receiving, by a first thread of the one or more multi-threaded processors, a first set of image frames associated with the gesture, the first set of image frames captured during a first time interval, performing, by the first thread, pose estimation on each frame of the first set of image frames including eliminating background information from each frame to obtain one or more areas of interest, storing information representative of the one or more areas of interest in a shared memory accessible to the one or more multi-threaded processors, and performing, by a second thread of the one or more multi-threaded processors, a gesture recognition operation on a second set of image frames associated with the gesture.

Abstract: In an exemplary embodiment, the present invention is an apparatus which includes at least one processor, and at least one memory including computer program code. The at least one memory and the computer program code are configured, with the at least one processor, to cause the apparatus to perform obtaining an image for segmentation; forming a trimap of at least a portion of the image, the trimap comprising a three-region map having a definite foreground, a definite background, and an unknown region separating the foreground and the background, said unknown region initially having a preselected width; in a plurality of iterations, changing the width of the unknown region; for each of the plurality of iterations, determining a quality measure; and selecting the width for the unknown region having the best quality measure. The apparatus may also include at least one camera for obtaining the image for segmentation.

Abstract: In accordance with some embodiments, methods, systems, and media for detecting the presence of are provided. In some embodiments, a method of detecting an analyte is provided, the method comprising: capturing an image of liquid crystals; determining one or more features based on the brightness of the pixels in the image; providing the one or more features to a trained support vector machine, wherein the support vector machine was trained using images captured of other liquid crystals when exposed to a first analyte and the other liquid crystals exposed to a second analyte; and receiving an indication from the support vector machine indicating whether the liquid crystals have been exposed to the first analyte.

Abstract: A shape estimating apparatus includes an acquiring unit and an estimating unit. The acquiring unit is configured to acquire a two-dimensional image. The estimating unit has artificial intelligence, and is configured to provide the artificial intelligence with the two-dimensional image and cause the artificial intelligence to estimate a three-dimensional shape of a subject of the two-dimensional image. A learning result of machine learning performed using learning data containing supervisor data expressing a three-dimensional shape of a sample subject and a sample two-dimensional image obtained by capturing an image of the three-dimensional shape of the sample subject is set to the artificial intelligence.

Abstract: A system may receive video data generated by a camera device positioned in a physical environment. The system may receive electromagnetic (EM) response signals generated by an array of 5G antenna devices. The system may refine the EM response signals. The system may determine location information for a metallic object. The system may generate a movement trajectory of the metallic object. The system may generate a feature vector comprising an aggregation of the refined EM response signals and the movement trajectory. The system may submit the feature vector to a machine learning framework. The system may classify the metallic object as a weapon. The system may generate a virtual render comprising a graphical indication of the metallic object. The system may combine the virtual render with the video input data and display the combined virtual render and video data.

Abstract: This application discloses a technology for flattening a photographed page of a book and straightening texts therein. The technology uses one or more mathematical models to represent a curved shape of the photographed page with certain parameters. The technology also uses one or more photographic image processing techniques to dewarp the photographed page using the parameters of the curved shape. The technology uses one or more additional parameters that represent certain features of the photographed page to dewarp the photographed page.

Abstract: A method of providing an accurate three-dimensional scan of a dental arch area is disclosed. The arch area has two segments and a connecting area between the two segments. The connecting area has homogeneous features. A connecting-geometry tool with at least one definable feature is affixed to the arch area. The definable feature overlays at least part of the connecting area. The arch area is scanned to produce a scanned dataset of the arch area. The definable feature of the connecting-geometry tool on the connection area is determined based on the scanned dataset. The dimensions of the arch area are determined based on the data relating to the definable features from the scanned dataset.

Abstract: A sensor calibration system configured to receive a first frame of one or more markers on a repositionable platform at a first location within a space from a sensor. The system is further configured to determine pixel locations in the first frame for a first marker and a second marker from among the one or more markers. The system is further configured to receive distance information that corresponds with a distance between the platform and distance measuring devices. The system is further configured to determine (x,y) coordinates for the first marker and the second marker based on the distance information. The system is further configured to generate a homography based on the (x,y) coordinates and pixel locations of the first marker and the second marker. The homography includes coefficients that translate between pixel locations in the first frame of the sensor and (x,y) coordinates in the global plane.

Abstract: A method, apparatus and computer program product are provided for warping a perspective image into the ground plane using a homography transformation to estimate a bird's eye view in real time. Methods may include: receiving first sensor data from a first vehicle traveling along a road segment in an environment, where the first sensor data includes perspective image data of the environment, and where the first sensor data includes a location and a heading; retrieving a satellite image associated with the location and heading; applying a deep neural network to regress a bird's eye view image from the perspective image data; applying a Generative Adversarial Network (GAN) to the regressed bird's eye view image using the satellite image as a target of the GAN to obtain a stabilized bird's eye view image; and deriving values of a homography matrix between the sensor data and the established bird's eye view image.

Abstract: Methods and systems for monitoring communication traffic in communication networks, such as Internet Protocol (IP) traffic transferred over the Internet or over a wireless network. The disclosed techniques identify communication traffic that is associated with target individuals, by extracting digital images from the traffic and recognizing target individuals who appear in the images. A correlation system monitors communication sessions that are conducted in a communication network to identify known target individuals who appear in images. Upon recognizing a target individual in an image extracted from a certain session, the system correlates this target user with one or more of the communication identifiers used in the session. The system automatically identifies IP addresses or other identifiers that are used by target individuals, and enable subsequent tracking of such identifiers.