Abstract: A face recognition system including: a reading unit that reads identification information from a medium carried by an authentication subject; an image capturing unit that acquires an image; a face detection unit that detects, as a detected face image, a face image from the image acquired; a face matching unit that, when a registered face image associated with the identification information read by the reading unit is present, matches the detected face image against the registered face image and matches, against the registered face image, the detected face image captured before the reading unit reads the identification information; and a registration unit that, when the registered face image associated with the identification information read is not present, registers, as the registered face image, the detected face image before the reading unit reads the identification information.

Abstract: Embodiments of this application disclose a foreground data generation method performed at a computer device. The method includes: obtaining a background image and a target image, the target image containing a target object and a background; removing the background from the target image according to the background image and the target image, to obtain initial foreground data of the target object in the target image; obtaining certain foreground data and uncertain data from the initial foreground data, wherein the uncertain data represents data whose value is between the certain foreground data and background data corresponding to the background; and segmenting the certain foreground data from the uncertain data, to obtain target foreground data of the target object in the target image.

Abstract: An example operation may include one or more of receiving, by an accident processing node, an accident report from a transport, determining, by an accident processing node, a time and location parameters of the accident based on the report, querying, by an accident processing node, transport profiles on a storage based on the time and location parameters, and responsive to the transport profiles containing data corresponding to the time and location parameters, sending a request to access the transport profiles.

Abstract: The technology relates to controlling a vehicle in an autonomous driving mode. For example, sensor data identifying a plurality of objects may be received. Pairs of objects of the plurality of objects may be identified. For each identified pair of objects of the plurality of objects, a similarity value which indicates whether the objects of that identified pair of objects can be responded to by the vehicle as a group may be determined. The objects of one of the identified pairs of objects may be clustered together based on the similarity score. The vehicle may be controlled in the autonomous mode by responding to each object in the cluster in a same way.

Abstract: One example method includes accessing an appearance history of a person, the appearance history including information concerning an appearance of a person at a particular time, generating, based on the appearance history, a forecast that comprises a probability that the person will appear again at some future point in time, determining that the probability meets or exceeds a threshold, and updating a high probability group database to include a facial image of a face of the person.

Abstract: An apparatus for controlling docking with a spacecraft includes at least one camera for generating at least one image pixel stream of the spacecraft. A field programmable gate array (FPGA) receives the at least one image pixel stream from the at least one camera. The FPGA texture processes the at least one pixel stream to generate at least one texture map for the at least one image pixel stream. A processor receives the at least one texture map from the FPGA and calculates texture map statistics responsive to the generated at least one texture map, generates thresholding results for the at least one pixel image stream responsive to the generated at least one texture map, determines a bus centroid of the spacecraft responsive to the generated thresholding results and outputs the determined bus centroid of the spacecraft. A docking controller controls docking of with the spacecraft responsive to the determined bus centroid of the spacecraft.

Abstract: Methods for providing a location of an object or objects of interest that may be performed by a processor of a computing device may include generating a map of an environment around the computing device by a first simultaneous location and mapping (SLAM) operation using information received from the optical sensor, identifying an object of interest in the environment of the computing device by an object recognition operation using information received from the optical sensor, determining a location of the object or objects of interest in the environment, and presenting the determined location of the object or objects of interest in the environment in response to a trigger event correlated to the object or objects of interest.

Abstract: Automating conversion of drawings to indoor maps and plans. One example is a computer-implemented method of determining a geo-location, the method comprising: determining a floor-level outline of a floor depicted in a CAD drawing; receiving an approximate geo-location of a building to which the CAD drawing applies; obtaining an overhead image of a target area encompassing the approximate geo-location, the overhead image comprising a plurality of buildings within the target area; identifying a plurality of building footprints within the target area; calculating, by a device, a plurality of distance functions that relate the floor-level outline to the each of the plurality of building footprints, the calculating creates a plurality of similarity scores; selecting a building footprint from plurality of building footprints, the selecting based on the plurality of similarity scores; and calculating a final geo-location of the building corresponding to the building footprint.

Abstract: A video quality assessment apparatus and method are provided. The video quality assessment apparatus includes a memory storing one or more instructions; and a processor configured to execute the one or more instructions stored in the memory to: identify whether a frame included in a video is a fully-blurred frame or a partially-blurred frame based on a blur level of the frame, obtain, in response to the frame being the fully-blurred frame, an analysis-based quality score with respect to the fully-blurred frame; obtain, in response to the frame being the partially-blurred frame, a model-based quality score with respect to the partially-blurred frame; and process the video based on at least one of the analysis-based quality score or the model-based quality score to obtain a processed video.

Abstract: A method of processing an image within a vehicle interior with a camera includes acquiring a live image of the vehicle interior. The live image is compared to an ideally aligned image of the vehicle interior having an associated region of interest to generate a homography matrix. The homography matrix is applied to the region of interest to generate a calibrated region of interest projected onto the live image for detecting an object therein.

Abstract: An electronic device may be provided with optical markers. A marker may be formed from a coating. The coating may be patterned to form a two-dimensional optical code or may be patterned to form an outline or other recognizable marker structure that helps provide information about an electronic device. A device with a sensor such as a depth sensor or other sensor may gather information on the electronic device and its markers. This information may include information on images captured with an image sensor while the electronic device is illuminated by one or more light beams from the depth sensor or other light sources. Markers may be configured to serve as mixed reality optical markers in a mixed reality system. Analysis of the mixed reality marker images or other sensor data may reveal information on device type, device location, device size, device orientation, and other information on a marked device.

Abstract: Provided are an imaging device, an image recording device, and an imaging method capable of recording an important moment. An imaging device includes an imaging unit and a changing unit. The imaging unit captures an image of the surroundings, and generates image data. The changing unit changes the frame rate of an image captured by the imaging unit in accordance with the degree of possibility that a predetermined event occurs, which is predicted based on the image data.

Abstract: A remote control for controlling a medical apparatus having at least one driven movable components is provided. The remote control comprises a sensor configured to detect a position and a motion of the remote control, and at least one release switch. The remote control is configured to emit a control signal capable of controlling a motion of the at least one driven movable component according to a motion of the remote control detected by the sensor when a control of the motion of the at least one driven movable component is released by actuating the at least one release switch.

Abstract: Surveillance systems process video streams obtained by a surveillance device, such as a drone, to either obscure or highlight objects in a surveillance area based on tags associated with the objects. A method of providing obscurant data includes receiving image data including an image of a target and receiving a preference setting corresponding to the target. Obscurant data of at least a portion of the image data corresponding to the target are determined using the received preference setting. A method of providing surveillance image data includes capturing image data including an image of a target, querying a database to receive a preference setting corresponding to the target, determining the obscurant data of the portion of the image data, and selectively modifying the received image data according to the determined obscurant data to provide the surveillance image data.

Abstract: Methods, systems, and apparatus for an infrared and visible imaging system. In some implementations, Image data from a visible-light camera is obtained. A position of a device is determined based at least in part on the image data from the visible-light camera. An infrared camera is positioned so that the device is in a field of view of the infrared camera, with the field of view of the infrared camera being narrower than the field of view of the visible-light camera. Infrared image data from the infrared camera that includes regions representing the device is obtained. Infrared image data from the infrared camera that represents the device is recorded. Position data is also recorded that indicates the location and pose of the infrared camera when the infrared image data is acquired by the infrared camera.

Abstract: A tracking device includes a processor including hardware, and the processor sets a start frame, extracts multiple representative points of a contour of a tracking target, tracks the extracted multiple representative points, performs outlier determination based on an interrelationship of the tracked multiple representative points, performs a process of removing an outlier representative point determined to be an outlier, and extracts new representative points based on multiple representative points after the process of removing the outlier representative point when a given condition is met.

Abstract: Presented herein are systems and methods for generating a multi-view focused video stream. The methods involve obtaining at least one video stream of a first participant in an online video communication session between at least the first participant at a first endpoint and a second participant at a second endpoint; determining a bounding region of at least one element in the video stream; generating a focused video stream from the video stream that includes a focused view of the at least one element within the bounding region; and presenting the focused video stream on the second endpoint to at least the second participant.

Abstract: Embodiments of this application disclose a video data processing method and apparatus, and a storage medium. The method includes determining, in response to a trigger operation on a target video, a target pixel in a key video frame, and obtaining multimedia information associated with the target pixel, the key video frame being a video frame in which the trigger operation is located, and the target pixel corresponding to the trigger operation in the key video frame; identifying a trajectory obtaining request corresponding to the target pixel based on location information of the target pixel; obtaining target trajectory information associated with the location information of the target pixel, the target trajectory information comprising location information of the target pixel in a next video frame following the key video frame; and displaying the multimedia information based on the location information of the target pixel in the next video frame.

Abstract: A security camera with a motion detection function, which comprises: an image sensor, configured to capture original images; a variation level computation circuit, configured to compute image variation levels of the original images; a long term computation circuit, configured to calculate a first average level for the image variation levels corresponding to M of the original images; a short term computation circuit, configured to calculate a second average level for the image variation levels corresponding to N of the original images, wherein M>N; and a motion determining circuit, configured to determine whether a motion of an object appears in a detection range of the image sensor according to a relation between the first average level and the second average level. By such security camera, the interference caused by noise or small object can be avoided. Accordingly, the motion detection of the security camera can be more accurate.

Abstract: The present disclosure relates to systems, methods, and computer-readable media for selectively identifying image frames from an input video to provide to an image processing model based on camera statistics. For example, systems disclosed herein include receiving an input video and associated camera statistics from a video capturing device. The systems disclosed herein further include identifying select image frames to provide to the image processing model based on the camera statistics and based on an application of the image processing model. The systems disclosed herein further include selectively identifying and providing camera statistics to the image processing model. By selectively providing data to the image processing model based on camera statistics, the systems disclosed herein can leverage capabilities of video capturing devices to significantly reduce the expense of processing resources when utilizing a variety of image processing models.

Abstract: Provided are an animation generation method, apparatus, and system and a storage medium, relating to the field of animation technology. The method includes acquiring the real feature data of a real object, where the real feature data includes the action data and the face data of the real object during a performance process; determining the target feature data of a virtual character according to the real feature data, where the virtual character is a preset animation model, and the target feature data includes the action data and the face data of the virtual character; and generating the animation of the virtual character according to the target feature data. The performance of the real object is used for generating the animation of the virtual character.

Abstract: A system including a first luminaire housing, a second luminaire housing, and a controller. The first luminaire housing includes a first light source configured to provide illumination to a first location, and a first I/O device configured to sense a first data set corresponding the first location. The second luminaire housing is separate from the first luminaire housing and includes a second light source configured to provide illumination to a second location, and a second I/O device configured to sense a second data set corresponding to the second location. The controller is configured to receive a portion of the first data set and a portion of the second data set, combine the portion of the first data set and the portion of the second data set to form a third data set corresponding to the first location and second location, and output the third data set.

Abstract: A computer system for digital video alarm guard tour monitoring. The computer system includes a computer having non-transitory memory for storing machine instructions that are to be executed by the computer. The machine instructions when executed by the computer implement the following functions: receiving one or more guard tour parameters; identifying a plurality of digital frames in response to the one or more guard tour parameters; motion analyzing the plurality of digital frames to detect motion between the plurality of digital frames; object analyzing the plurality of digital frames to detect an object and an object class of the object in response to detecting the motion; and transmitting a guard tour event and the plurality of digital frames to an alarm server in response to determining the object class is associated with an alarm analytics tag.

Abstract: A method for representing virtual information in a view of a real environment comprises providing a virtual object having a global position and orientation with respect to a geographic global coordinate system, with first pose data on the global position and orientation of the virtual object, in a database of a server, taking an image of a real environment by a mobile device and providing second pose data as to at which position and with which orientation with respect to the geographic global coordinate system the image was taken. The method further includes displaying the image on a display of the mobile device, accessing the virtual object in the database and positioning the virtual object in the image on the basis of the first and second pose data, manipulating the virtual object or adding a further virtual object, and providing the manipulated virtual object with modified first pose data or the further virtual object with third pose data in the database.

Abstract: Systems and processes generate a viewing experience by determining location data and movement data of (a) at least one object and (b) at least one participant within an event area. A three-dimensional model of the event area, the participant and the object is determined based upon the location data and the movement data. A viewpoint of a spectator defines an origin, relative to the three-dimensional model, and a direction of the viewing experience. The viewing experience is generated for the viewpoint at least in part from the three-dimensional model to include one or more of augmented reality, mixed reality, extended reality, and virtual reality.

Abstract: Systems, apparatuses, and methods are described which provide a camera system. A camera is in communication with a positioning device. The positioning device has a compass, gyroscope, and emits an infrared light beam. The camera has a sensor that receives reflected and/or scattered infrared light from a moving target. The camera changes its focus, zoom, and/or angle of a field of view of the camera based on information from its sensor, and gyroscope and compass information from the positioning device and/or camera.

Abstract: The present disclosure is directed to systems and methods for generating investigations of user behavior. In an example embodiment, the system includes a video camera configured to capture video of user activity, a video analytic module to perform real-time video processing of the captured video to generate non-video data from video, and a computer configured to receive the video and the non-video data from the video camera. In some embodiments, the video camera is at least one of a traffic camera or an aerial drone camera. The computer includes a video analytics module configured to analyze one of video and non-video data to identify occurrences of particular user behavior, and an investigation generation module configured to generate an investigation containing at least one video sequence of the particular user behavior. In some embodiments, the investigation is generated in near real time.

Abstract: A processing method that is performed by one or more processor is provided. The processing method includes determining a target video frame in a currently captured video; determining an object area in the target video frame based on a box selection model; determining a category of a target object in the object area based on a classification model used to classify an object in the object area; obtaining augmented reality scene information associated with the category of the target object; and performing augmented reality processing on the object area in the target video frame and the augmented reality scene information, to obtain the augmented reality scene.

Abstract: Methods, apparatus, systems and articles of manufacture to generate temporal representations for action recognition systems are disclosed. An example apparatus includes an optical flow computer to compute first optical flows for a video based on computing differences between pairs of frames of the video; an evolution of trajectories (EoT) generator to generate EoT temporal representations of the video based on (a) computing second optical flows of the video and (b) aggregating ones of the second optical flows having different time spans; an action identifier to: identify first actions in the video based on the first optical flows; identify second actions in the video based on the EoT temporal representations; and identify third actions in the video based on frames of the video; and a fuser to determine a fourth action based on a weighted average of the first actions, second actions, and third actions.

Abstract: A method of an optical sensor device includes: automatically entering a calibration mode to automatically define a region of interest as a masking region; and, selectively ignoring a motion detected within the masking region when the optical sensor device is in a normal operation mode.

Abstract: Techniques for displaying comments relative to a video frame are described herein. The disclosed techniques include receiving a frame of a video; receiving bullet screen data comprising a plurality of comments associated with the frame; receiving a mask frame data segment corresponding to the frame; determining a mask area based on the mask frame data segment, wherein the mask area corresponds to a main area of the frame; and displaying the plurality of comments relative to the frame in areas other than the mask area.

Abstract: Digital object animation techniques are described. In a first example, translation-based animation of the digital object operates using control points of the digital object. In another example, the animation system is configured to minimize an amount of feature positions that are used to generate the animation. In a further example, an input pose is normalized through use of a global scale factor to address changes in a z-position of a subject in different digital images. Yet further, a body tracking module is used to computing initial feature positions. The initial feature positions are then used to initialize a face tracker module to generate feature positions of the face. The animation system also supports a plurality of modes used to generate the digital object, techniques to define a base of the digital object, and a friction term limiting movement of features positions based on contact with a ground plane.

Abstract: There are provided methods and systems for estimating the mass of one or more occupants in a vehicle cabin comprising obtaining multiple images of the one or more occupants, comprising a sequence of 2D (two dimensional) images and 3D (three dimensional) images of the vehicle cabin captured by an image sensor, applying a pose detection algorithm on each of the obtained sequences of 2D images to yield one or more skeleton representations of said one or more occupants and combining the one or more 3D images of said sequence of 3D images with said one or more skeleton representations of said one or more occupants to yield skeleton models and analyze the skeleton models to extract one or more features of each of the one or more occupants and further process the one or more extracted features of the skeleton models to estimate the mass of the one or more occupants.

Abstract: Methods, systems, and computer readable media for providing personalized saliency models, e.g., for use in mixed reality environments, are disclosed herein, comprising: obtaining, from a server, a first saliency model for the characterization of captured images, wherein the first saliency model represents a global saliency model; capturing a first plurality of images by a first device; obtaining information indicative of a reaction of a first user of the first device to the capture of one or more images of the first plurality images; updating the first saliency model based, at least in part, on the obtained information to form a personalized, second saliency model; and transmitting at least a portion of the second saliency model to the server for inclusion into the global saliency model. In some embodiments, a user's personalized (i.e., updated) saliency model may be used to modify one or more characteristics of at least one subsequently captured image.

Abstract: Embodiments relate to a companion animal identification method including acquiring a preview image for capturing a face of a target companion animal, checking if the face of the target companion animal is aligned according to a preset criterion, capturing the face of the target companion animal when it is determined that the face of the target companion animal is aligned, and identifying the target companion animal by extracting features from a face image of the target companion animal having an aligned face view, and an identification system for performing the same.

Abstract: An object tracking system that includes a sensor and a tracking system. The sensor is configured to capture a frame of at least a portion of a rack within a global plane for a space. The tracking system is further configured to receive the frame, to determine a pixel location for the first person, and to determine a person is within the predefined zone associated with the rack. The tracking system is further configured to identify the plurality of items in a digital cart associated with the person, to identify an item from the digital cart associated with the first person, and to remove the identified item from the digital cart associated with the person.

Abstract: An information processing apparatus includes a reception unit configured to receive, from a plurality of image capturing apparatuses, at least one of information about designation of a subject by a user, information about automatic subject detection, and information about a manual operation on an image capturing lens by the user, a determination unit configured to determine a main image capturing apparatus and a sub image capturing apparatus from among the plurality of image capturing apparatuses, based on the information received by the reception unit, and a transmission unit configured to transmit a result of the determination to the main image capturing apparatus and transmit subject information set in the main image capturing apparatus to the sub image capturing apparatus.

Abstract: Techniques for distributed object detection and tracking are described. In an example method, a first current frame from a series of frames is sent to a first node, for detection of a first object. After object detection information for the first object is received in return, a second node is selected, and a second current frame is sent to the second node for an updated object detection. In addition, while waiting for the results of the updated object detection, two or more frames following the second current frame are sent to respective tracking nodes. Object modelling information indicating location and/or classification of one or more objects, as derived from the previously received object detection information is also sent to each of the respective tracking nodes. Tracking information for the first object is received from each of the respective tracking nodes.

Abstract: This present disclosure relates to a subject recognition method and apparatus, an electronic device, and a computer-readable storage medium. The method includes: obtaining a current image frame and detecting whether there is a moving subject in the current image frame; when there is no moving subject in the current image frame, obtaining a motion state transition condition; when the current image frame satisfies the motion state transition condition, obtaining a target subject in a previous image frame; and determining a target subject in the current image frame based on the target subject in the previous image frame.

Abstract: Provided are a mobile device (100) and computer-implemented method (700) for localisation in an existing map of a 3-D environment. For a first image frame, a first pose is localised based on visual features. For a second image frame, a pose is predicted (810) based on inertial measurements, combined with the pose of the first image frame. Based on the predicted pose, the method predicts (830) a set of landmarks that are likely to be visible. A second pose is then calculated (850), for the second image frame, based on matching (840) visual features of the second image frame to the set of landmarks.

Abstract: A photographing method applied to an electronic device includes: when a camera of the electronic device is started to perform photographing, the electronic device displays a first viewfinder frame, and displays a first preview picture. When a zoom magnification used by the electronic device increases to be greater than a preset zoom magnification, the electronic device displays the first viewfinder frame and a second viewfinder frame. The first viewfinder frame displays a second preview picture, and the second viewfinder frame displays a third preview picture, and a viewfinder range of the camera corresponding to the third preview picture is greater than a viewfinder range of the camera corresponding to the second preview picture.

Abstract: A compact first-person-view (FPV) pan and tilt camera mount is installed in a remote-controlled vehicle, and the vehicle is configured to accommodate a video processing module/air unit, a camera module, and a horizontal and vertical rotatable (pan and tilt) camera mount module. A realistic scale remote-controlled scale vehicle typically comes with interior cabin or cockpit space to accommodate driver/pilot that can be utilized to install the pan & tilt camera module. The video processing module is configured to process images shot by the camera module. The camera is mounted on the pan and tilt module. The pan and tilt module includes a first servo, a base, a movable seat, a rotation module, a clamp portion, and an accommodation portion. The first servo has a first shaft, the movable seat has a fitting seat, and the fitting seat has a connection orifice. The rotation module has a first semi-circular gear and a second semi-circular gear meshing.

Abstract: A method of operating a server providing a sports video-based platform service includes tracking a ball by using a pre-processing of leaving dynamic pixels in the sports video of a ball game, determining an unidentified player associated with a score-related scene of the sports video by using a ball tracking result, identifying the unidentified player by tracking the unidentified player up to an adjacent frame where the unidentified player is identifiable, and generating a time section of the sports video and identification information for the unidentified player, corresponding to the score-related scene.

Abstract: Provided is an artificial intelligence (AI) system that mimics functions, such as recognition and determination by human brains, by utilizing a machine learning algorithm, such as deep learning, and applications of the AI system.

Abstract: A hearing aid comprises a sensor configured for detecting a focus of an end user on a real sound source, a microphone assembly configured for converting sounds into electrical signals, a speaker configured for converting the electrical signals into sounds, and a control subsystem configured for modifying the direction and/or distance of a greatest sensitivity of the microphone assembly based on detected focus. A virtual image generation system comprises memory storing a three-dimensional scene, a sensor configured for detecting a focus of the end user on a sound source, a speaker configured for conveying sounds to the end user, and a control subsystem configured for causing the speaker to preferentially convey a sound originating from the sound source in response to detection of the focus, and for rendering image frames of the scene, and a display subsystem configured for sequentially displaying the image frames to the end user.

Abstract: The present invention relates to a tracker and a surveying apparatus comprising the tracker, which improve the reliability of tracking a target. The tracker comprises a first imaging region having a plurality of pixels for taking a first image of a scene including the target; a second imaging region having a plurality of pixels for taking a second image of a scene including the target; a control unit to receive a timing signal indicating a time duration during which an illumination illuminating the target in the scene is switched on and off, control the first imaging region to take the first image of the scene when the timing signal indicates that the illumination unit is switched on, and control the second imaging region to take the second image when the illumination is switched off; and a read out unit configured to read out the first image from the first imaging region and the second image from the second imaging region and to obtain a difference image.

Abstract: An image processing method and an electronic device. The method includes: in a case that the electronic device is in a first movement state, capturing a first image through the first camera, where the first camera moves relative to the body; displaying the first image on a shooting preview interface; and in a case that the electronic device changes from the first movement state to a stationary state, processing a second image and updating the first image on the shooting preview interface to the processed second image, where the second image is an image captured by the second camera in a case that the electronic device is in the stationary state, and the second camera is stationary relative to the body. The embodiments of the present disclosure are applied to a process of processing an image when the electronic device changes from a movement state to a stationary state.

Abstract: A machine learning scheme can be trained on a set of labeled training images of a subject in different poses, with different textures, and with different background environments. The label or marker data of the subject may be stored as metadata to a 3D model of the subject or rendered images of the subject. The machine learning scheme may be implemented as a supervised learning scheme that can automatically identify the labeled data to create a classification model. The classification model can classify a depicted subject in many different environments and arrangements (e.g., poses).

Abstract: Systems of presenting environmental data include a frequency emitting device, a frequency receiving device, wherein the frequency receiving device is tuned to receive a reflected signal from the frequency emitting device, a processor, and a sound emitting device adapted to play a sound transmission. The processor is programmed to compile data from the reflected signal and convert the data from the reflected signal into a sound transmission.

Abstract: A tracking device includes a processor including hardware. The processor is configured to: set a start frame and an end frame in a video including multiple frames; perform forward tracking in frames subsequent to the start frame based on a region of a tracking target in the start frame; perform backward tracking in frames previous to the end frame based on a region of the tracking target in the end frame; and generate a combined mask image by combining a forward mask image based on the forward tracking with a backward mask image based on the backward tracking.