Abstract: A face recognition method includes generating a target face recognition model, performing face detection on an image to obtain a first face image, and performing face recognition on the first face image in the image by using the target face recognition model to obtain a first face feature. Generating the target face recognition model includes determining a training sample, the training sample comprising a training face image calibrated with identity information, and training a general face recognition model by using the training sample, and updating a parameter of the general face recognition model based on a training target to obtain the target face recognition model, the training target being a prediction result of the general face recognition model predicting identity information of a new training face image in the training sample to be the calibrated identity information of the training face image in the training sample.

Abstract: A method and apparatus for predicting an object of interest of a user receives an input image of a visible region of a user and gaze information including a gaze sequence of the user, generates weight filters for a per-frame segmentation image by analyzing a frame of the input image for input characteristics of the per-frame segmentation image and the gaze information, and predicts an object of interest of the user by integrating the weight filters and applies the integrated weight filter to the per-frame segmentation image.

Abstract: An information processing apparatus includes an acquisition unit that acquires information indicating an estimation result of movement of a predetermined target object in accordance with a history of chronological detection results of positions of the target object and a recognition result of a surrounding environment of the target object, and a control unit that causes display information to be presented in a display mode corresponding to the estimation result.

Abstract: Embodiments of the present disclosure provide a method and an apparatus for clock synchronization, a device, a storage medium and a vehicle. The method includes: determining a first pose change of an image acquirer with respect to a reference coordinate system at different image acquisition time points; determining a second pose change of a calibration acquirer with respect to the reference coordinate system at different corrected image acquisition time points, in which, the different corrected image acquisition correction time points are determined according to the different image acquisition time points and each predetermined correction time variable; and performing a clock synchronization on the image acquirer and the calibration acquirer according to the first pose change of the image acquirer and the second pose change of the calibration acquirer corresponding to the each correction time variable.

Abstract: Generally discussed herein are examples of gesture-based extended reality (XR) with object recognition and tracking. A method, implemented by an extended reality (XR) device can include recognizing and tracking one or more objects in the image data, recognizing a gesture in the image data, analyzing the image data to determine whether a condition is satisfied, the condition indicating a recognized and tracked object of the one or more objects proximate which the recognized gesture is to be made, and in response to determining that the condition is satisfied, performing an augmentation of the image data based on satisfaction of the condition.

Abstract: A method for computing dimensions of an object in a scene includes: controlling, by a processor, a depth camera system to capture at least a frame of the scene, the frame including a color image and a depth image arranged in a plurality of pixels; detecting, by the processor, an object in the frame; determining, by the processor, a ground plane in the frame, the object resting on the ground plane; computing, by the processor, a rectangular outline bounding a projection of a plurality of pixels of the object onto the ground plane; computing, by the processor, a height of the object above the ground plane; and outputting, by the processor, computed dimensions of the object in accordance with a length and a width of the rectangular outline and the height.

Abstract: Examples of the present disclosure disclose data processing methods, apparatuses and storage media. The data processing method includes: obtaining a plurality of video images of a target site within a predetermined time range; performing pedestrian identification processing on the plurality of video images to obtain, based on the identification result, a customer counting result for a first region in the target site and a customer counting result for a second region in the target site; and determining a degree of association between the second region and the first region based on the customer counting result for the first region and the customer counting result for the second region.

Abstract: The present invention relates to a novel method and system for crater detection in planetary data based on marked point processes (MPP), effective for various object detection tasks in Earth observation, and for planetary image registration. The resulting spatial features are exploited for registration, together with fitness functions based on the MPP energy, on the mean directed Hausdorff distance, and on the mutual information. Two different methods—one based on birth-death processes and region-of-interest analysis, and the other based on graph cuts and decimated wavelets—are included within the present framework. Experimental results confirmed the effectiveness of the present invention in terms of crater detection performance and sub-pixel registration accuracy.

Abstract: The present teaching relates to method, system, medium, and implementations for understanding a three dimensional (3D) scene. Image data acquired by a camera at different time instances with respect to the 3D scene are received wherein the 3D scene includes a user or one or more objects. The face of the user is detected and tracked at different time instances. With respect to some of the time instances, a 2D user profile representing a region in the image data occupied by the user is generated based on a corresponding face detected and a corresponding 3D space in the 3D scene is estimated based on calibration parameters associated with the camera. Such estimated 3D space occupied by the user in the 3D scene is used to dynamically update a 3D space occupancy record of the 3D scene.

Abstract: Embodiments of the present disclosure provide a method and device for recognizing a state of an electrical device. The method includes obtaining an image of the electrical device in a field, wherein the electrical device is disposed on a plane of a predefined polygon in the field; obtaining an original appearance image of the electrical device in the field by recovering the predefined polygon in the image to an original appearance of the predefined polygon; and determining the state of the electrical device based on the original appearance image of the electrical device in the field.

Abstract: A clothing item being captured is appropriately measured without requiring a dedicated sheet of paper or the like.

Abstract: There is disclosed a computer implemented eye tracking system and corresponding method and computer readable storage medium, for detecting three dimensional, 3D, gaze, by obtaining at least one head pose parameter using a head pose prediction algorithm, the head pose parameter(s) comprising one or more of a head position, pitch, yaw, or roll; and to input the at least one head pose parameter along with at least one image of a user's eye, generated from a 2D image captured using an image sensor associated with the eye tracking system, into a neural network configured to generate 3D gaze information based on the at least one head pose parameter and the at least one eye image.

Abstract: Provided are a method and a device that can efficiently generate a training dataset.

Abstract: A method for generating a segmentation of an image that assigns each pixel to a respective segmentation category from a set of segmentation categories is described. The method includes obtaining features of the image, the image including a plurality of pixels. For each of one or more time steps starting from an initial time step and continuing until a final time step, the method includes generating a network input from the features of the image and a current segmentation output as of the time step, processing the network input using a convolutional recurrent neural network to generate an intermediate segmentation output for the time step, and generating an updated segmentation output for the time step from the intermediate segmentation output for the time step and the current segmentation output as of the time step. The method includes generating a final segmentation of the image from the updated segmentation output.

Abstract: A method for evaluating a gastrointestinal tract may include characterizing one or more disease parameters using objective measures obtained from imaging data of a gastrointestinal tract. The one or more disease parameters reflect a measure of at least one of lesions, ulcers, bleeding, stenosis, and vasculature. The method may also include using the one or more characterized disease parameters to classify a disease state.

Abstract: Augmented reality devices and methods for computing a homography based on two images. One method may include receiving a first image based on a first camera pose and a second image based on a second camera pose, generating a first point cloud based on the first image and a second point cloud based on the second image, providing the first point cloud and the second point cloud to a neural network, and generating, by the neural network, the homography based on the first point cloud and the second point cloud. The neural network may be trained by generating a plurality of points, determining a 3D trajectory, sampling the 3D trajectory to obtain camera poses viewing the points, projecting the points onto 2D planes, comparing a generated homography using the projected points to the ground-truth homography and modifying the neural network based on the comparison.

Abstract: Certain aspects of the present disclosure provide methods and apparatus for signaling a receive antenna mode to use during beamforming training procedure. For example, an apparatus for wireless communications, may generally include a processing system configured to generate a first frame having one or more beamforming training fields to be output for transmission to a wireless device using a directional transmit antenna mode and an indication whether the wireless device is to be in an Omni-directional receive antenna mode to receive the one or more beamforming training fields, and a first interface configured to output the first frame for transmission.

Abstract: Within many applications impulse radio based ultra-wideband (IR-UWB) transmission offers significant benefits for very short range high data rate communications when compared with existing standards and protocols. In many of these applications the main design goals are very low power consumption and very low complexity design for easy integration and cost reduction. Digitally programmable IR-UWB transmitters using an on-off keying modulation scheme on a 0.13 microns CMOS process operating on 1.2 V supply and yielding power consumption as low as 0.9 mW at a 10 Mbps data rate with dynamic power control are enabled. The IR-UWB transmitters support new frequency hopping techniques providing more efficient spectrum usage and dynamic allocation of the spectrum when transmitting in highly congested frequency bands. Biphasic scrambling is also introduced for spectral line reduction.

Abstract: Target tracking methods and apparatuses, electronic devices, and storage media are provided. The method includes: obtaining features of a plurality of reference images of a target image; determining a plurality of initial predicted positions of a tracking target in the target image based on the features of the plurality of reference images; and determining a final position of the tracking target in the target image based on the plurality of initial predicted positions.

Abstract: A face direction estimation device (10) includes a face image acquiring unit (11) acquiring a shot face image, a face detecting unit (12) detecting the face position in the face image, a face organ detecting unit (13) detecting face organs in the detected face position, a switching determining unit (14) evaluating the detected face organs, and switching between first and second face direction estimating methods in accordance with the evaluation, a first face direction estimating unit (15) estimating the face direction in accordance with a positional relationship among the detected face organs when the switching determining unit switches to the first face direction estimating method, and a second face direction estimating unit (16) calculating a face movement amount on the basis of the detected face position and estimating the face direction in accordance with the movement amount when the switching determining unit switches to the second face direction estimating method.