Abstract: The present invention discloses methods and systems for detecting a human body in an image using a machine learning model. The method includes selecting one or more candidate regions from one or more regions in an image based on a pre-defined threshold. Then, a body is detected in a candidate region of the one or more candidate regions, based on a set of pair-wise constraints. The body detection further includes detection of various body parts. Thereafter, a score is computed for each detected body part and a final score for the candidate region is computed, based on the scores of the detected body parts.

Abstract: The present invention discloses methods and systems for detecting a human body in an image using a machine learning model. The method includes selecting one or more candidate regions from one or more regions in an image based on a pre-defined threshold. Then, a body is detected in a candidate region of the one or more candidate regions, based on a set of pair-wise constraints. The body detection further includes detection of various body parts. Thereafter, a score is computed for each detected body part and a final score for the candidate region is computed, based on the scores of the detected body parts.

Abstract: A method includes capturing at least one screenshot of a display screen including an initial screenshot. The method includes removing text from the initial screenshot to generate a base image. The method includes identifying a background of the initial screenshot as a closed region. The method includes, for each of the at least one screenshots: storing a time of capturing the screenshot; identifying text, text color, and text location in the screenshot; identifying each closed region in the screenshot that is different from the background of the initial screenshot, and a region color and region location for each identified closed region in the screenshot; storing the region color and the region location for each identified closed region; and storing the text color and the text location of the identified text.

Abstract: A method and system for managing nitrogen applied by nitrogen application equipment to a geographic region includes determining a growth stage for the geographic region using a crop module, and determining a nitrogen change for the geographic region based on the growth stage using a nitrogen change module, which can additionally or alternatively include determining an amount of nitrogen initially available for a geographic region.

Abstract: In an approach to determining pavement markings, a computer determines a location of a first computing device based on data received from one or more location devices associated with the first computing device. The computer then retrieves pavement marking data for one or more pavement markings for the location and determines whether one or more existing pavement markings are present at the location. Responsive to determining that one or more existing pavement markings are present at the location, the computer determines whether each of the one or more existing pavement markings meet one or more pre-determined thresholds for an acceptable pavement marking quality. Furthermore, responsive to determining each of the one or more existing pavement markings do not meet the one or more pre-determined thresholds for an acceptable pavement marking quality level, the computer provides pavement marking data to the first computing device.

Abstract: Disclosed is see-through smart glasses (100) and see-through methods thereof. The see-through smart glasses (100) includes a model storing module (110), an image processing module (130) and an image displaying module (120). The model storing module (110) is used for storing a 3D model of a target; the image processing module (130) is used for identifying target extrinsic marker (210?) of the target (200) based on a user's viewing angle, find out a spatial correlation between the target extrinsic marker (210?) and internal structure (220) based on the 3D model of the target (200), and generating an interior image of the target (200) corresponding to the viewing angle based on the spatial correlation; and the image displaying module (120) is used for displaying the interior image.

Abstract: A computer-implemented method to compare events from videos is disclosed. The method may include monitoring two or more videos and identifying a first event in a first video of the two or more videos. The method may include determining a first feature description of the first event, a first location of the first event, and a first time stamp of the first event. The method may also include identifying a second event in a second video of the two or more videos. The method may include determining a second feature description of the second event, a second location of the second event, and a second time stamp of the second event. The method may include comparing the first feature description with the second feature description, the first location with the second location, and the first time stamp with the second time stamp.

Abstract: A method includes generating, with a mobile device having a camera, images of a portion of a real space containing an object having a position. The control device tracks the position of the object based at least on the images received from the mobile device. The control device monitors the position of the object for an event conforming to a rule specified at the control device. The event is based on the rule and the position of the object in the real space. The control device, or a client device, generates an indication that the event has been detected by the control device.

Abstract: The present disclosure relates to systems and methods for providing automatic, adaptive privacy for security and/or automation systems. In some embodiments, the method may include operating a plurality of video monitoring components of the security and/or automation system, and detecting a first occupant in a location associated with the security and/or automation system. The method may further include identifying the detected first occupant, and disabling at least one of the plurality of video monitoring components based at least in part on an inputted privacy preference associated with the first occupant.

Abstract: Solutions for object tracking problems are presented by gathering images using one or more cameras, processing the gathered images to generate a directed acyclic graph, using the directed acyclic graph to determine a path cover that achieves maximum weight and satisfies one or more positive or negative constraints, and using the path cover to solve the object tracking problem. A first set of solutions utilizes trellis graphs, a second set of solutions employs a greedy approach, and a third set of solutions uses search algorithms.

Abstract: A state acquisition unit (2020) acquires a state of a monitoring target in a captured image captured by a camera (3040). A monitoring point acquisition unit (2040) acquires, from a monitoring point information storage unit (3020), a monitoring point corresponding to the state of the monitoring target acquired by the state acquisition unit (2020). The monitoring point indicates a position to be monitored in the captured image. A presentation unit (2060) presents the monitoring point on the captured image.

Abstract: A computer-implemented method to identify an object in a video is disclosed. The method may include obtaining a video and receiving an indication of one or more foreground regions in the video from a user module based on a user selection within the user module. The method may also include receiving an indication of one or more regions of interest in the foreground regions from the user module based on a user selection within the user module. The method may include determining a human potential size in a plurality of locations in the one or more regions of interest. The method may include generating a background model based on a plurality of frames of the video. The method may also include tracking an object in the one or more regions of interest based on the background model. The method may include identifying the object as a predicted human based on the human potential size.

Abstract: An apparatus for video generation includes: a memory; and a processor coupled to the memory and configured to execute a road surface end detection process to detect, from an image including a road surface along which a vehicle travels, a road surface end of the road surface in a widthwise direction, execute a calculation process to calculate a distance from the vehicle to the road surface end, execute a generation process to generate, when the calculated distance is smaller than a given threshold value, a video for inducing a driver of the vehicle to steer to a direction in which the distance increases, and execute a display control process to cause a display apparatus to display the generated video.

Abstract: The present application discloses a method and apparatus for detecting a vehicle contour based on point cloud data. The method includes: acquiring to-be-trained point cloud data; generating label data corresponding to points in the to-be-trained point cloud data in response to labeling on the points in the to-be-trained point cloud, the labeling used to indicate whether each of the points in the to-be-trained point cloud data is on a vehicle contour; training a fully convolutional neural network model based on the points in the to-be-trained point cloud data and the label data corresponding to the points in the to-be-trained point cloud data, to obtain a vehicle detection model; and acquiring to-be-detected point cloud data, and obtaining a detection result corresponding to each to-be-detected point in the to-be-detected point cloud data based on the vehicle detection model. The implementation may achieve an accurate detection of the vehicle contour.

Abstract: An image processing apparatus acquires a detection area in an image coordinate system expressing an area of a target object acquired from within an image, and derives a target spatial area in which the detection area is transformed to a corresponding position in a spatial coordinate system that simulates actual space in which the target object is present. In addition, the image processing apparatus identifies a reference physical model that simulates characteristics related to behavior and shape of the target object in the spatial coordinate system. Next, the image processing apparatus compares the target spatial area and the reference physical model on the spatial coordinate system, and corrects position and shape of the target spatial area based on the comparison result. Then, the image processing apparatus transforms the corrected target spatial area to a corresponding position in the image coordinate system, and outputs corrected area information expressing the corrected area.

Abstract: Embodiments of the present disclosure relate to the field of shoe production. There provides a smart shoe which has an identification function. The smart shoe includes an upper, a shoe sole and a foot sole print recognition sensor disposed in the shoe sole; the foot sole print recognition sensor is configured to acquire foot sole print information of a user who wears the smart shoe.

Abstract: A method of host-directed illumination for verifying the validity of biometric data of a user is provided that includes capturing biometric data from a user with an authentication device during authentication and directing illumination of the biometric data from a host authentication system during the capturing operation. Moreover, the method includes comparing illumination characteristics of the captured biometric data against illumination characteristics expected to result from the directing operation, and determining that the user is a live user when the illumination characteristics of the captured biometric data match the illumination characteristics expected to result from the directing operation.

Abstract: A prelam layer for use in forming a laminated card includes a flexible circuit substrate; a fingerprint sensor disposed on the flexible circuit substrate, the fingerprint sensor having upper and bottom surfaces, the bottom surface of the fingerprint sensor being disposed on the substrate, an active layer of the fingerprint sensor disposed towards the upper surface of the fingerprint sensor; a first integrated circuit chip disposed on the substrate and having at least one lead electrically connected to the flexible circuit substrate; and an adapter flexible circuit electrically bonded to the active layer of the fingerprint sensor. The integrated circuit chip is adapted to communicate with the fingerprint sensor through the adapter flexible circuit.

Abstract: A vehicle includes a camera directed generally toward a driver seat of the vehicle. The camera captures images within a passenger compartment of the vehicle. A text recognition module is communicatively coupled to the camera and recognizes text characters in the captured images. An electronic processor is communicatively coupled to the text recognition module and interprets the recognized text characters as text information, categorizes the text information, and enters the text information into an application within the vehicle.

Abstract: An image recognition unit of the present disclosure includes: a plurality of memory sections; a writing section that selectively writes a plurality of pieces of pixel data of a data map to the plurality of memory sections; and an arithmetic section that reads a plurality of pixel data sets from the plurality of memory sections, and determines whether an input image corresponding to the data map includes a recognition object, on a basis of the plurality of pixel data sets, the pixel data sets each including a predetermined number of pieces of pixel data.

Abstract: An apparatus and method for detecting a foreground in an image is provided, and the foreground detecting apparatus includes a context information estimator configured to estimate context information on a scene from an image frame of the image, a background model constructor configured to construct a background model of the image frame using the estimated context information, and a foreground detector configured to detect a foreground from the image frame based on the constructed background model.

Abstract: A computer-implemented method (40) of reducing processing time of an application for visualizing image data, the application being one of a plurality of applications selectable by a user and each of the plurality of applications comprising a pre-processing algorithm for pre-processing the image data.

Abstract: Embodiments of the present invention provide a method of determining whether data exceeds a validity range of an operation, comprising dividing operation data indicative of a range of validity of the operation into a plurality of chunks, determining a partial convex hull for each of the plurality of chunks, determining a convex hull for the operation data based on the plurality of partial convex bulls, and determining whether the data exceeds the validity range of the operation data based on the convex hull.

Abstract: An image analyzing unit of an image retrieving device capable of retrieving an image using a local feature quantity includes: an input unit configured to input an image; a reception unit configured to receive designation of a retrieval condition corresponding to a retrieval source image via a user interface; a selection unit configured to select a retrieval method on the basis of the retrieval condition; a calculation unit configured to calculate a local feature quantity of an image on the basis of the selected retrieval method; and a comparison unit configured to compare a local feature quantity of a retrieval target image with a local feature quantity of the retrieval source image.

Abstract: The present disclosure discloses an electronic coaster, comprising at least one first imaging sensor to capture at least one first image of a beverage present in a beverage holder placed on the electronic coaster, at least one second imaging sensor to capture at least one second image of ambience around the electronic coaster and a computing unit to receive the at least one first image and the at least one second image, process spectrum of the at least one first and second image for obtaining spectral signature of the beverage and compare the spectral signature of the beverage with predefined spectral signature of plurality of beverages to identify type of the beverage.

Abstract: An apparatus and a method. The apparatus includes a dynamic vision sensor (DVS) configured to generate a stream of events, where an event includes a location and a binary value indicating a positive or a negative change in luminance; a sampling unit connected to the DVS and configured to sample the stream of events; and an image formation unit connected to the sampling unit and configured to form an image for each sample of the stream of events, wherein a manner of sampling by the sampling unit is adjusted to reduce variations between images formed by the image formation unit.

Abstract: A photographing method and an apparatus include: using two photographing modules to acquire images of a to-be-photographed object at a first moment and a second moment after a preset time interval, and determining a distance of the to-be-photographed object according to image points formed by a point of the to-be-photographed object on photosensitive devices of the two photographing modules, and parameters of the two photographing modules; calculating a variation between the distances of the to-be-photographed object at the first moment and the second moment; determining whether the variation is less than or equal to a preset value; and photographing the to-be-photographed object if yes.

Abstract: A method for compressing an image, includes: calculating a level of hues of the image over at least all of one layer of the image; depending on the type of hues of the representative layer, classifying the image in one of the following three classes: a first class if the image is of a graphics type; a second class if the image is of a highly contrasted type; a third class if the image is of a low-contrasted type; and, choosing a compression processing type depending on the class of the image: difference processing, if the image is of the first class; frequency processing, if the image is of the third class; and, if the image is of the second class: for lossless or low-loss compression, preferably using difference processing, and, in the other cases preferably using frequency processing.

Abstract: A system and method for subject-matching in images comprises detecting a first orientation of a first subject in a target image; comparing the first orientation with a second orientation of a second subject in a source image to obtain at least one orientation parameter; extracting at least one features from the target image; computing a visual similarity score between the target image and the source image using the features, the visual similarity score being computed as a function of the at least one feature and the at least one orientation parameter; and determining a match between the first subject and the second subject in accordance with the visual similarity score.

Abstract: An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. The learned dictionaries may be derived using efficient convolutional sparse coding to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of images over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detect geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.

Abstract: Techniques are described for performing multi-stage image classification. For example, multi-stage image classification can comprise a first classification stage and a second classification stage. The first classification stage can determine an overall classification for an input image (e.g., based on a relative entropy result calculated for the input image). The second classification stage can be performed by dividing the image into a plurality of blocks and classifying individual blocks, or groups of blocks, based on a classification model that is specific to the overall classification of the image determined in the first classification stage.

Abstract: A computer-implemented method to train a video annotation machine learning process is disclosed. The method may include obtaining a video and determining that a predetermined event occurs in the video. The method may include identifying a first set of object attribute data associated with the event in the video based on a machine learning process and machine learning data. The method may include receiving a second set of object attribute data of the event in the video from a user or external source. The method may also include comparing the first set of object attribute data with the second set of object attribute data. The method may include validating the quality of the first set of object attribute data when the first set of object attribute data is determined to be sufficiently similar to the second set of object attribute data.

Abstract: Systems and methods are disclosed for segregating target individuals represented in a probe digital image from background pixels in the probe digital image. In particular, in one or more embodiments, the disclosed systems and methods train a neural network based on two or more of training position channels, training shape input channels, training color channels, or training object data. Moreover, in one or more embodiments, the disclosed systems and methods utilize the trained neural network to select a target individual in a probe digital image. Specifically, in one or more embodiments, the disclosed systems and methods generate position channels, training shape input channels, and color channels corresponding the probe digital image, and utilize the generated channels in conjunction with the trained neural network to select the target individual.

Abstract: A first conveyance unit and a second conveyance unit functioning as pre-processing conveyance units provided in a pre-processing device and conveying the IC tag continuous body by suctioning it to conveyance belts, a second tractor feeder unit functioning as a print-processing tractor feeder unit provided in a printing device and conveying the IC tag continuous body by engaging and disengaging feed pins in sprocket holes formed in the IC tag continuous body, and a fourth conveyance unit functioning as a post-processing conveyance unit provided in a post-processing device and conveying the IC tag continuous body by suctioning it to a conveyance belt are provided.

Abstract: According to an embodiment, an image forming system comprises a terminal device and an image forming apparatus. The image forming apparatus is provided with an image forming section, a transfer section and a transfer bias applying section. The image forming section forms a toner image on a transfer belt. The transfer section transfers the toner image onto a medium. The transfer bias applying section applies transfer bias voltage to the transfer section. The terminal device is provided with a request receiving section and a bias voltage determination section. The request receiving section receives a print request of printing the image on at least one card arranged on a cardboard as media. The bias voltage determination section determines the transfer bias voltage according to the print request.

Abstract: A printing apparatus includes a reception unit that receives outline information representing an outline of a character, a generation unit that generates, using the outline information, a bitmap including pixels corresponding to the character, the pixels being associated with a graphic attribute, a changing unit that refers an attribute associated with a pixel adjacent to one of the pixels corresponding to the character, and changes a density value of the adjacent pixel associated with the referred attribute being different from a graphic attribute and a character attribute to a density which is based on a density value of the one pixel, and a printing unit that prints an image based on the bitmap after the change.

Abstract: A method of inserting a data structure into a component using a 3D printer is provided. The method includes providing the data structure having at least one structural parameter associated with the component, converting the data structure into indicia representative of the data structure, and manufacturing the component containing the indicia.

Abstract: Described is in particular a method of generating a transfer pattern (110) defining a digital code pattern. According to the described method, a digital code pattern definition (104) defining a plurality of light and dark portions is received, wherein each of such portion has a size A. The transfer pattern (110) is generated by rasterizing the digital code pattern definition (104) with structure pixels, in particular by mapping the digital code pattern definition into an array of equally sized structure pixels, wherein the size A of the light and dark portions is an integer multiple of a size B of the structure pixels. The array of structure pixels comprises at least two different types of structure pixels. Each type of structure pixel defines a certain surface structure on the rubber article, the surface structure causing a certain optical reflectivity of the structure pixel. Further, at least two types of structure pixels have a different optical reflectivity.

Abstract: A sticker for attaching to at least one part of a machine having at least one rotating component that is to be monitored. The sticker provides a machine-readable label, such as a Quick Response (QR) code or bar code, which contains information about the component, such as a serial number of the component, and a processor arranged to collect information concerning the use of the at least one rotating component and/or the machine and a transmitter that is arranged to automatically transmit the collected information if/when the processor collects information that a temperature of the at least one part of the machine having at least one rotating component being monitored exceeds a predetermined temperature or a vibration of the at least one part of the machine being monitored exceeds a predetermined level. The transmitted collected information is arranged to be associated with the machine-readable label.

Abstract: A multi-smartcard may include: a support; a touchscreen disposed on the support configured to receive an input operation from a user including a first input operation and a second input operation; and a processor configured to generate a first user interface (UI) of card information corresponding to the input operation applied to the touchscreen and instruct the touch screen to display the first UI, and to receive the first and second input operations, wherein the processor is configured to change the card category in response to receiving the first input operation and change the card type in response to receiving the second input operation.

Abstract: A smart multi-card may include: a frame; a wireless communication unit configured to transmit or receive data to or from a card terminal or a communication device through wireless communication; an information storage unit configured to store card information relating to a plurality of cards; a user input unit configured to receive a user input from a user to select card information corresponding to one of the plurality of cards; a display unit configured to visually display the selected card information; and a processor configured to extract the card information selected by the user from the information storage unit, process the card information, deliver the processed card information to the display unit, and process the data transmitted or received through the wireless communication unit.

Abstract: An IC card includes a communication unit and a controller. The communication unit can communicate with one communication destination by a plurality of interfaces including a first interface and a second interface. The controller processes a command received by the communication unit, and makes the communication unit transmit a response to the command. In a case where the first interface becomes unavailable after the communication unit receives the command by the first interface until the communication unit transmits the response to the command, the controller makes the communication unit transmit a response containing discontinuation information indicating that the transmission of the response to the command received by the first interface is discontinued by the second interface.

Abstract: A document includes a sensor, at least one antenna, a first processor, a second processor, storage, and a switch. The first processor is configured to communicate with an external reading device via the antenna. The switch is configured to switch the antenna between a first stable state in which a communication is prevented between the first processor and the reading device, and a second stable state, in which a communication is possible between the first processor and the reading device. The sensor is configured to detect a first identification feature of a user of the document. The second processor is configured to compare the first identification feature with a second identification feature saved in the storage, wherein the second processor is configured to switch the switch to a second state if there is conformity between the first identification feature and the second identification feature.

Abstract: A radio frequency identification tag including a stretchable substrate (105) and an antenna (110) having a plurality of substantially concentric loops (140) disposed on the substrate is described. A radius of curvature of the antenna along at least 90% of each loop of the antenna may be greater than about 0.1 mm and less than about 5 mm. The antenna includes a first terminal (124) disposed within an inner-most loop (145) of the antenna and a second terminal (126) disposed outside an outermost loop (147) of the antenna (110). The first terminal (124) is in electrical communication with a first end (120) of the antenna and the second terminal (126) is in electrical communication with a second end (122) of the antenna. The radio frequency identification tag may include an electrode making electrical connections with the first and second terminals.

Abstract: A computer program product and method provides a question and answer service that accepts an initial first question from a user and analyzes the question by a first generation subsystem to generate a first answer. A second generation subsystem of the question and answer service is configured to generate a second question based at least in-part on keywords from the first question and the first answer.

Abstract: Embodiments of the present invention provide a method for feature extraction comprising generating synaptic connectivity information for a neurosynaptic core circuit. The core circuit comprises one or more electronic neurons, one or more electronic axons, and an interconnect fabric including a plurality of synapse devices for interconnecting the neurons with the axons. The method further comprises initializing the interconnect fabric based on the synaptic connectivity information generated, and extracting a set of features from input received via the electronic axons. The set of features extracted comprises a set of features with reduced correlation.

Abstract: Provided in some embodiments is an artificial intelligence (“AI”) engine configured to work with a pedagogical programming language configured to enable an author to 1) define a mental model to be learned by an AI model, the mental model including an input, one or more concept nodes, one or more stream nodes, and an output, as well as 2) define one or more curriculums for training the AI model respectively on the one or more concept nodes. A compiler can be configured to generate an assembly code from a source code authored in the pedagogical programming language. An architect module can be configured to propose a neural-network layout from the assembly code. A learner module can be configured to build the AI model the neural-network layout. An instructor module can be configured to train the AI model on the one or more concept nodes respectively with the one or more curriculums.

Abstract: Described invention and its embodiments, in part, facilitate discovery of ‘Most Recent Common Ancestors’ in the family trees between a massive plurality of individuals who have been predicted to be related according to amount of deoxyribonucleic acids (DNA) shared as determined from a plurality of 3rd party genome sequencing and matching systems.

Abstract: Provided herein in some embodiments is an artificial intelligence (“AI”) engine hosted on one or more remote servers configured to cooperate with one or more databases including one or more AI-engine modules and one or more server-side client-server interfaces. The one or more AI-engine modules include an instructor module and a learner module configured to train an AI model. An assembly code can be generated from a source code written in a pedagogical programming language describing a mental model of one or more concept modules to be learned by the AI model and curricula of one or more lessons for training the AI model. The one or more server-side client-server interfaces can be configured to enable client interactions from a local client such as submitting the source code for training the AI model and using the trained AI model for one or more predictions.

Abstract: A recognition apparatus and a training method are provided. The recognition apparatus includes a memory configured to store a neural network including a previous layer of neurons, and a current layer of neurons that are activated based on first synaptic signals and second synaptic signals, the first synaptic signals being input from the previous layer, and the second synaptic signals being input from the current layer. The recognition apparatus further includes a processor configured to generate a recognition result based on the neural network. An activation neuron among the neurons of the current layer generates a first synaptic signal to excite or inhibit neurons of a next layer, and generates a second synaptic signal to inhibit neurons other than the activation neuron in the current layer.