Abstract: It is intended to allow an orientation of a mobile device observed in imaging data to be more appropriately specified. There is provided an information processing device (100) including an acquisition unit (111c) that acquires the imaging data and a direction specification unit (111c) that analyzes the imaging data to specify the orientation of the mobile device observed in the imaging data.

Abstract: An illumination device with projector includes a projector having a projection optical system, a projector holding section configured to hold the projector, a stand part to be coupled to the projector holding section, and a shade which is configured to cover a periphery of the projector holding section, and is provided with a projection opening through which projection light emitted from the projector is transmitted. The projector holding section is provided with an angle adjustment mechanism for changing a tilt angle of the projector centering on an end portion at an exit side of the projector.

Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for three-dimensional object tracking includes, in at least one aspect, a method including: obtaining three-dimensional positions of objects registered by a detection system configured to allow more false positives so as to minimize false negatives, forming hypotheses using a filter that allows connections between registered objects when estimated three-dimensional velocity vectors roughly correspond to an object in motion in three-dimensional space, eliminating a proper subset of the hypotheses that are not further extended during the forming, specifying at least one three-dimensional track of at least one ball in motion in three-dimensional space by applying a full three-dimensional physics model to data for the three-dimensional positions used in the forming of at least one hypothesis that survives the eliminating, and outputting for display the at least one three-dimensional track of the at least one ball in motion in thr

Abstract: An apparatus and method for inline scanned image enrichment is provided. The apparatus includes a computing device configured to receive a plurality of subject data, generate a candidate set to model the scan focal points from, digitally capture the slide using the identified focal points through machine-learning processes, processing the captured image to optimize its viewability, and storing the captured image in an accessible repository.

Abstract: Systems and methods are provided for enhanced animation generation based on using motion mapping with local bone phases. An example method includes accessing first animation control information generated for a first frame of an electronic game including local bone phases representing phase information associated with contacts of a plurality of rigid bodies of an in-game character with an in-game environment. Executing a local motion matching process for each of the plurality of local bone phases and generating a second pose of the character model based on the plurality of matched local poses for a second frame of the electronic game.

Abstract: Techniques for generating a visual response to a user input are described. A system may receive a natural language input and use a machine learning model to determine a first component is to determine a response to the natural language input while a second component is to determine supplemental content related to the natural language input. The system may receive, from the first component, first image data corresponding to the response. The system may also receive, from the second component, second image data corresponding to the supplemental content. The system may send, to a display, a command to present the first image data and the second image data.

Abstract: Techniques for tracing back a projectile to the projectile origin are described. A method includes detecting projectile track(s) in image(s). Each projectile track crosses multiple pixels in each image. The projectile track(s) correspond to projectile(s). The projectile track(s) in the image(s) are translated to traceback path(s). The traceback path includes a known location and a projectile origin (e.g. the location at which the projectile originated, also termed the shooter's location).

Abstract: A method and apparatus for sorting is described, and which includes providing a product stream formed of individual objects of interest having feature aspects which can be detected; generating multiple images of each of the respective objects of interest; classifying the feature aspects of the objects of interest; identifying complementary images by analyzing some of the multiplicity of images; fusing the complementary images to form an aggregated region representation of the complementary images; and sorting the respective objects of interest based at least in part upon the aggregated region representation which is formed.

Abstract: An intelligent three dimensional scanner system mountable on a movable machine, including three dimensional scanner, a camera, and control circuitry. The control circuitry is configured to receive three dimensional point data from the three dimensional scanner, receive two dimensional image data from the camera, input the two dimensional image data to a machine learning model, which identifies objects in the two dimensional image data, fuse the three dimensional point data with the identified objects in the two dimensional image data in order to identify the objects in the three dimensional point data, and control a scan pattern to direct scanning resolution of the three dimensional scanner based on the identified objects.

Abstract: An information processing method includes receiving a user input, the user input representing a trajectory, performing recognition on the trajectory to obtain a matching result based on matching in a database, recording the trajectory to generate an image including the trajectory, and outputting a candidate option. The candidate option includes the matching result and an identifier of an image.

Abstract: A camera module, according to an embodiment of the present invention, comprises: a light emitting unit for outputting an optical signal to an object; a light receiving unit for receiving the optical signal reflected from the object; and a control unit for controlling the light emitting unit such that the optical signal selectively has one optical pattern from among a surface light source pattern and a point light source pattern. The light emitting unit comprises: a light emitting element array on which a plurality of light emitting elements are arranged in accordance with a predetermined arrangement pattern; and a lens module for transmitting the optical signal output by the light emitting element array, wherein the lens module includes an optical element which duplicates the optical signal output by the light emitting element array.

Abstract: Disclosed are a method for counting regional population, a computer device and a computer readable storage medium. The method for counting regional population includes: acquiring an image to be analyzed in a target region; detecting a position of each first human body part in the image to be analyzed; determining, according to the position of each first human body part in the image to be analyzed and a first transformation relation, a physical position of each first human body part in the target region; and determining the population in each sub-region according to a relative positional relation between the position of the first human body part in the image to be analyzed and the sub-image, as well as a relative positional relation between the physical position of the first human body part and the sub-region.

Abstract: In some embodiments, an electronic device emphasizes and/or deemphasizes user interfaces based on the gaze of a user. In some embodiments, an electronic device defines levels of immersion for different user interfaces independently of one another. In some embodiments, an electronic device resumes display of a user interface at a previously-displayed level of immersion after (e.g., temporarily) reducing the level of immersion associated with the user interface. In some embodiments, an electronic device allows objects, people, and/or portions of an environment to be visible through a user interface displayed by the electronic device. In some embodiments, an electronic device reduces the level of immersion associated with a user interface based on characteristics of the electronic device and/or physical environment of the electronic device.

Abstract: An occupant monitoring device for a vehicle includes a display, a controller, and an imager. The display is configured to display an operation screen for an occupant in the vehicle. The controller is configured to execute control based on an operation type determined as an operation performed by the occupant on the operation screen of the display. The imager is configured to image the occupant in the vehicle. The controller is configured to avoid executing the control based on the determined operation type in a case where the operation type performed by the occupant at least involves movement toward the imager.

Abstract: An evaluation method for a computer to execute a process includes, acquiring a plurality of pieces of skeleton information in time series based on position information of joints of an object that executes a plurality of motions; specifying a transition period between a first motion and a second motion that follows the first motion, which are included in the plurality of motions based on the plurality of pieces of skeleton information; determining whether the transition period is related to a certain combination of motions by inputting skeleton information among the plurality of pieces of skeleton information that corresponds to the transition period into an evaluation model trained to evaluate a transition period between motions based on a plurality of pieces of skeleton information in time series; and outputting an evaluation result of the transition period by the evaluation model.

Abstract: A system and method for generating a stained image including the steps of obtaining a first image of a key sample section; and processing the first image with a multi-modal stain learning engine arranged to generate at least one stained image, wherein the at least one stained image represents the key sample section stained with at least one stain.

Abstract: An information processing apparatus acquires editing target image data including video image data, acquires first display image data of a plurality of frames, generates second display image data of a plurality of frames determined in accordance with the number of frames of the first display image data from the editing target image data, and displays display images of a plurality of frames indicated by the second display image data of the plurality of frames on a display. The editing target image data and the first display image data of the plurality of frames are image data having a common attribute. The second display image data of the plurality of frames includes second display image data for video images of a plurality of frames corresponding to still image data of a plurality of frames constituting at least a part of the video image data.

Abstract: A method provided for 3D object localization predicts pairs of 2D bounding boxes. Each pair corresponds to a detected object in each of the two consecutive input monocular images. The method generates, for each detected object, a relative motion estimation specifying a relative motion between the two images. The method constructs an object cost volume by aggregating temporal features from the two images using the pairs of 2D bounding boxes and the relative motion estimation to predict a range of object depth candidates and a confidence score for each object depth candidate and an object depth from the object depth candidates. The method updates the relative motion estimation based on the object cost volume and the object depth to provide a refined object motion and a refined object depth. The method reconstructs a 3D bounding box for each detected object based on the refined object motion and refined object depth.

Abstract: In one aspect, a method of outputting a representation of data is described. The method is executed by a digital electronic processor communicatively coupled to at least one display device and comprises receiving a dataset comprising a plurality of data items, each data item comprising one or more parameters. In response to determining that a first representation of the plurality of data items fits within a display area of the at least one display device, outputting the first representation to the display area. In response to determining that the first representation exceeds the display area: determining one or more clusters of data items by performing a clustering analysis based on at least one of the one or more parameters, wherein the or each cluster of data items corresponds to a sub-region of the display area.

Abstract: In a sales area, a method for checking the layout of articles in a gondola, the gondola comprising at least one electronic shelf label which corresponds to a matching area of a gondola, with a single product slot field comprising a gondola number, a row number and a shelf label number, the method comprising steps of: acquisition of an image of the gondola; automated detection of electronic shelf labels, and automated detection of rows; for at least one electronic shelf label, determination of the matching area of the gondola, and determination of the slot field; detection of layout information in said area of the gondola in the acquired image; identification of the associated article identifier in a realogram database; and check of compliance of detected layout information, with respect to expected layout information stored in the realogram database.

Abstract: A system includes: a unit that input a series image sequence; a unit that selects a reference image; a unit that selects a proximity image; and an inference unit that recognizes the reference image and the proximity image by performing inference processing, including convolution processing and activation function processing, on the reference image and the proximity image. The inference unit generates results of performing the convolution processing and the activation function processing on the proximity image from the results of the convolution processing and the activation function processing performed on the reference image, and the results of the product of the results of the convolution processing performed on a difference image, which is an image of the difference between the reference image and the proximity image, and a derivative value of the results of the convolution processing and the activation function processing performed on the reference image.

Abstract: In various examples, historical trajectory information of objects in an environment may be tracked by an ego-vehicle and encoded into a state feature. The encoded state features for each of the objects observed by the ego-vehicle may be used—e.g., by a bi-directional long short-term memory (LSTM) network—to encode a spatial feature. The encoded spatial feature and the encoded state feature for an object may be used to predict lateral and/or longitudinal maneuvers for the object, and the combination of this information may be used to determine future locations of the object. The future locations may be used by the ego-vehicle to determine a path through the environment, or may be used by a simulation system to control virtual objects—according to trajectories determined from the future locations—through a simulation environment.

Abstract: There is provided a method for measuring anatomical features of a body, comprising obtaining a video having a plurality of frames; analyzing each frame of the video to detect the position of each anatomical feature; if necessary, calculating the distance travelled between frames of an anatomical feature using a predetermined reference object within the video (e.g., the true length between one's knee and hip); and if necessary, using the raw video and extracted features to predict a biomechanical output, and/or calculating summary metrics from the aggregate data from the video.

Abstract: A method for determining authenticity of a video in a surveillance system, whereby a sequence of image frames of a scene is captured, and an object is tracked. A current image quality measure in an image area corresponding to the tracked object is determined in at least a first and second image frame. chosen such that the object has moved at least a predetermined distance between the first and second image frames. A current image quality measure variation for the object is determined, the image quality measure variation describing the image quality measure as a function of position of the object in the image frames. The current image quality measure variation is compared to a known image quality measure variation. In response to the current image quality measure variation deviating from the known pixel density variation by less than a predetermined amount, it is determined that the video is authentic.

Abstract: A method includes obtaining, using at least one processor, audio/video content. The method also includes processing, using the at least one processor, the audio/video content with a trained attention-based machine learning model to classify the audio/video content. Processing the audio/video content includes, using the trained attention-based machine learning model, generating a global representation of the audio/video content based on the audio/video content, generating a local representation of the audio/video content based on different portions of the audio/video content, and combining the global representation of the audio/video content and the local representation of the audio/video content to generate an output representation of the audio/video content. The audio/video content is classified based on the output representation.

Abstract: A system for anomaly detection in a self-checkout environment, comprising a processing unit for receiving transaction data from a self-checkout terminal: characterising an activity based on a set of features extracted from the received transaction data; defining a plurality of active intervals for each characterised activity; determining a meta-feature vector for each defined active interval of the plurality of active intervals; comparing each meta feature vector with a predefined set of vectors; and determining an anomaly based on the comparison.

Abstract: A method for determining a movement of a device relative to at least one object based a digital image sequence of the object recorded from the location of the device. The method includes computing a plurality of optical flow fields from image pairs of the digital image sequence; finding the position of an object in a partial image region in the most current image in each case and assigning the partial image region to the object; forming a plurality of partial optical flow fields from the plurality of optical flow fields; selecting a partial flow fields from the plurality of partial flow fields in accordance with at least one criterion to facilitate the estimation of a change in scale of the object; and estimating the change in scale for the at least one object using the assigned partial image region based on the selected partial flow field.

Abstract: A method to stabilize image capture for a camera device (110). The method includes capturing, at an auxiliary frame rate and using an auxiliary imaging element (112) rigidly coupled with the camera device (110), auxiliary images of a light source (143) attached to an object (142), where the auxiliary frame rate exceeds a camera frame rate of the image capture (1211); detecting each of a plurality of locations of the light source (143) in a corresponding one of the auxiliary images (1212); analyzing the plurality of locations to generate a measure of uncontrolled movement (1213); and adjusting, based at least on the measure of uncontrolled movement, the camera device (110) during the image capture of the object by the camera device (110) at the camera frame rate (1214).

Abstract: A visualized image display device includes an acquisition means for acquiring time-series feature data in which time-series data of a feature of an object in a video and an object ID are associated with each other, and classification data in which the object ID and a class ID labeled to the object are associated with each other; a selection means for selecting a class ID to be visualized, and a display control means for acquiring the object ID associated with the selected class ID from the classification data, acquiring time-series data associated with the acquired object ID from the time-series feature data, and on the basis of the acquired time-series data, displaying a feature image representing a temporal change of the feature of the object having the selected class ID, on a display unit.

Abstract: A system and method for selecting image sequences of echocardiogram studies for visual comparison by a user. The method includes receiving image sequences from a current study and a prior study to be compared. The method includes determining a relevant view of the image sequences of the current and prior studies and selecting an image sequence from one of the current and prior studies to a user via an interactive comparison panel. The method includes determining which image sequence of the relevant view of an other of the current and prior studies that most closely matches the selected image sequence via the interactive comparison panel.

Abstract: Systems and methods are provided for navigating a host vehicle. In an embodiment, a processing device may be configured to receive images captured over a time period; analyze images to identify a target vehicle; receive map information associated including a plurality of target trajectories; determine, based on analysis of the images, first and second estimated positions of the target vehicle within the time period; determine, based on the first and second estimated positions, a trajectory of the target vehicle over the time period; compare the determined trajectory to the plurality of target trajectories to identify a target trajectory traversed by the target vehicle; determine, based on the identified target trajectory, a position of the target vehicle; and determine a navigational action for the host vehicle based on the determined position.

Abstract: A prediction device f includes an acquisition unit and a prediction unit. The acquisition unit is configured to acquire attribute data pertaining to the plurality of exhibits and the number of visitors to each of the plurality of exhibits during a first period in the display area in which the plurality of exhibition articles are exhibited. The prediction unit is configured to predict a future flow of persons to the plurality of exhibits by a prediction model. The prediction model is generated using attribute data for a second period that is a period previous to the first period, graph time-series data pertaining to a change over time in a movement pattern for each of the plurality of visitors to the plurality of exhibits during the second period, the number of visitors to the exhibits, and the number of visitors to each of the plurality of exhibits.

Abstract: A multi-modal sensor system includes: an underlying sensor system; a polarization camera system configured to capture polarization raw frames corresponding to a plurality of different polarization states; and a processing system including a processor and memory, the processing system being configured to control the underlying sensor system and the polarization camera system, the memory storing instructions that, when executed by the processor, cause the processor to: control the underlying sensor system to perform sensing on a scene and the polarization camera system to capture a plurality of polarization raw frames of the scene; extract first tensors in polarization representation spaces based on the plurality of polarization raw frames; and compute a characterization output based on an output of the underlying sensor system and the first tensors in polarization representation spaces.

Abstract: A method of calculating a size of a Gaussian kernel in a crowd counting system. The method includes dividing a crowd density map into several areas at equal intervals; calculating an estimated value of average distance of k nearest heads with respect to a head center point coordinate of a current person; calculating a weight coefficient for an average distance of k nearest heads; calculating a size of a Gaussian kernel corresponding to the head center point coordinate of the current person; determining whether there are any head center point coordinates of which sizes of Gaussian kernels have not been calculated yet in training data. If there are head center point coordinates of which sizes of the Gaussian kernels have not been calculated in the training data, recalculating an estimated value of average distance of k nearest heads with respect to another head center point coordinate of another current person.

Abstract: An imaging system can obtain image data, for instance from an image sensor. The imaging system can supply the image data as input data to a machine learning system, which can generate one or more maps based on the image data. Each map can identify strengths at which a certain image processing function is to be applied to each pixel of the image data. Different maps can be generated for different image processing functions, such as noise reduction, sharpening, or color saturation. The imaging system can generate a modified image based on the image data and the one or more maps, for instance by applying each of one or more image processing functions in accordance with each of the one or more maps. The imaging system can supply the image data and the one or more maps to a second machine learning system to generate the modified image.

Abstract: Systems and methods are described for identifying, using a sensor, a location of an object in an environment, and determining a classification of the object. A human may be identified in proximity with the object, an identity of the human may be determined, and a determination may be made that a hazardous condition may occur, based on a combination of the location of the object, the classification of the object, and the identity of the human in proximity with the object. In response to determining that the hazardous condition may occur, an augmented reality scene associated with the potentially hazardous condition associated with the object may be generated for presentation, at a user device.

Abstract: A human detection device configured to analyze a fisheye image obtained by a fisheye camera installed above a to-be-detected area to detect a person existing in the to-be-detected area includes a head detector configured to detect at least one head candidate from the fisheye image by using an algorithm for detecting a human head, a human body detector configured to detect at least one human body candidate from the fisheye image by using an algorithm for detecting a human body, and a determining unit configured to determine, as a person, a pair satisfying a prescribed condition among pairs of the head candidate and the human body candidate formed of a combination of a detection result from the head detector and a detection result from the human body detector.

Abstract: Provided are a GPS coordinates-based target overall planning method and a camera. Said method comprises: acquiring the GPS coordinates of each tracking target (S101); for each pre-divided region, counting the number of tracking targets located in the region based on the acquired GPS coordinates of each tracking target (S102); generating a heat map of the tracking targets based on the number of the tracking targets in each region (S103). Hence, in the present method, a device generates a heat map based on the GPS coordinates of tracking targets, and the heat map can reflect the number of the tracking targets in each region, achieving the overall planning of the tracking targets.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for visual authentication. In some implementations, a method may include obtaining images of a person at a property; detecting a discontinuity in an appearance of the person in the images of the person at the property; determining that the discontinuity does not correspond to a known occlusion; and providing an indication of a potential spoofing attack.

Abstract: A computer vision method and computer vision system can be used to process a time-based series of images. For a subject image of the time-based series, a light intensity value is identified for each pixel of a set of pixels of the subject image. A light intensity threshold is defined for the subject image based on a size of a bounding region for an object detected within a previous image of the time-based series captured before the subject image. A modified image is generated for the subject image by one or both of: reducing the light intensity value of each pixel of a lower intensity subset of pixels of the subject image that is less than the light intensity threshold, and increasing the light intensity value of each pixel of a higher intensity subset of pixels of the subject image that is greater than the light intensity threshold.

Abstract: A moving target tracking device includes a position information creation unit that creates camera position information indicating adjacency relationships of a plurality of reference cameras and a plurality of pivoting cameras, a tracking target analysis unit that detects traveling information indicating a speed and a traveling direction of a moving target, a tracking score calculation unit that calculates a tracking score indicating a proportion at which the moving target has been able to be captured in the entire tracking section, a machine learning unit that creates, as record information, a control result obtained by a learning device that has learned a control value of each pivoting device corresponding to the traveling information such that the tracking score becomes higher, and a control information creation unit that creates control information by using the control value acquired with reference to the record information.

Abstract: Noise in measurement results of a laser distance measurement sensor is smoothed, and erroneous recognition of a position and a size of an object based on the measurement result is suppressed. An object recognition device according to the present invention recognizes the object by grouping the measurement results of the laser distance measurement sensor, calculates reliability of the recognition result thereof, and changes a time for continuously retaining the measurement result according to the reliability.

Abstract: An apparatus to facilitate inferred object shading is disclosed. The apparatus comprises one or more processors to receive rasterized pixel data and hierarchical data associated with one or more objects and perform an inferred shading operation on the rasterized pixel data, including using one or more trained neural networks to perform texture and lighting on the rasterized pixel data to generate a pixel output, wherein the one or more trained neural networks uses the hierarchical data to learn a three-dimensional (3D) geometry, latent space and representation of the one or more objects.

Abstract: Apparatuses, systems, and techniques to process luminance and/or radiance values of one or more images from one or more cameras using one or more neural networks to perform a machine vision task. In at least one embodiment, one or more neural networks determine detection difficulty levels of objects within the one or more images and performs a machine vision task based on the determined detection difficulty levels of objects within images associated with that ask.

Abstract: Systems and techniques are provided for generating one or more models. For example, a process can include obtaining a plurality of input images corresponding to faces of one or more people during a training interval. The process can include determining a value of the coefficient representing at least the portion of the facial expression for each of the plurality of input images during the training interval. The process can include determining, from the determined values of the coefficient representing at least the portion of the facial expression for each of the plurality of input images during the training interval, an extremum value of the coefficient representing at least the portion of the facial expression during the training interval. The process can include generating an updated bounding value for the coefficient representing at least the portion of the facial expression based on the initial bounding value and the extremum value.

Abstract: A first image can be acquired from a first sensor included in a vehicle and input to a deep neural network to determine a first bounding box for a first object. A second image can be acquired from the first sensor. Input latitudinal and longitudinal motion data from second sensors included in the vehicle corresponding to the time between inputting the first image and inputting the second image. A second bounding box can be determined by translating the first bounding box based on the latitudinal and longitudinal motion data. The second image can be cropped based on the second bounding box. The cropped second image can be input to the deep neural network to detect a second object. The first image, the first bounding box, the second image, and the second bounding box can be output.

Abstract: During an at least partially autonomous driving operation of a motor vehicle, an arrangement and mode of action of environmental sensors of the motor vehicle, the sensor data of which are used in the at least partially autonomous driving operation, is visualized by use of a display device arranged in the motor vehicle. The motor vehicle includes a data interface for wirelessly transmitting data to the display device.

Abstract: There is provided with an information processing apparatus. A display control unit displays, on an image, a polygon having vertices at respective positions of candidates for at least three detection targets in the image. A determining unit determines, as the at least three detection targets, the candidates for the at least three detection targets, based on user input. A calculating unit calculates a parameter for estimating a size of a detection target that corresponds to a respective position in the image, based on positions and sizes of the determined at least three detection targets.

Abstract: A method for determining motion information is provided to be executed by a computing device. The method includes: determining a first image and a second image, the first image and the second image each including an object; determining a first pixel region based on a target feature point on the object in the first image; determining a second pixel region according to a pixel difference among a plurality of first pixel points in the first pixel region and further according to the target feature point; and obtaining motion information of the target feature point according to the plurality of second pixel points and the second image, the motion information being used for indicating changes in locations of the target feature point in the first image and the second image.

Abstract: A method, device and apparatus for recognizing, categorizing and searching for a garment, and a storage medium. The method for recognizing a garment comprises: acquiring a target image containing a garment to be recognized, and determining, on the basis of the target image, a set of heat maps corresponding to key feature points contained in the target image, the set of heat maps comprising position probability heat maps corresponding to the respective key feature points contained in the target image (101); and processing the set of heat maps on the basis of a shape constraint corresponding to the target image, and determining position probability information of the key feature points contained in the target image (102).