Abstract: A first area and a second area are set for a first two-dimensional tomographic image where the first area and the second area overlap each other in a partial area in a horizontal direction of the first two-dimensional tomographic image. A positional deviation amount between the first two-dimensional tomographic image and a second two-dimensional tomographic image is obtained in each of the first area and the second area. A moving amount of the second two-dimensional tomographic image is determined with respect to the first two-dimensional tomographic image in an area where the first area and the second area overlap based on the positional deviation amount in the first area and the positional deviation amount the second area. Alignments are performed on the first two-dimensional tomographic image and the second two-dimensional tomographic image in an area where the first area and the second area overlap based on the moving amount.

Abstract: The present disclosure provides an obstacle detecting method and apparatus, a device and a storage medium, wherein the method comprises: obtaining a 3D point cloud collected by an unmanned vehicle during travel; projecting the 3D point cloud on a 2-dimensional grid to respectively obtain feature information of each grid; inputting the feature information of each grid into a pre-trained prediction model to respectively obtain obstacle prediction parameters of each grid; performing grid clustering according to the obstacle prediction parameters of each grid to obtain obstacle detection results. The solutions of the present disclosure can be applied to improve the accuracy of detection results.

Abstract: A computer-implemented method for assessing a building structure. The method includes receiving information indicative of captured data, the captured data comprising an image of the building structure. The method includes receiving information indicative of an analysis of the captured data. The method includes based on the analysis of the captured data, performing an assessment of the one or more examined regions. Performing the assessment includes determining one or more classifications each corresponding to a different one of the one or more examined regions, and determining one or more indicators each corresponding to a different one of the one or more classifications. The method includes determining a mapping of the one or more indicators to the one or more examined regions. The method includes providing for display the one or more indicators overlaid onto the image according to the determined mapping.

Abstract: Disclosed are systems and methods for image segmentation using convolutional networks. Image data comprising an image hypervolume can be received. The image hypervolume can be provided to a trained convolutional neural network (CNN). The CNN can output a segmentation of the image hypervolume.

Abstract: A neural network system for identifying positions of objects in an input image can include an object detector neural network, a memory interface subsystem, and an external memory. The object detector neural network is configured to, at each time step of multiple successive time steps, (i) receive a first neural network input that represents the input image and a second neural network input that identifies a first set of positions of the input image that have each been classified as showing a respective object of the set of objects, and (ii) process the first and second inputs to generate a set of output scores that each represents a respective likelihood that an object that is not one of the objects shown at any of the positions in the first set of positions is shown at a respective position of the input image that corresponds to the output score.

Abstract: A device includes memory and a processor. The device receives biometric information. The device receives location information. The device analyzes the received biometric information with stored biometric information. The device analyzes the received location information with stored location information. The device determines whether the received biometric information matches the stored biometric information. The device determines whether the received location information matches the stored location information. The device sends an electronic communication that indicates whether the received biometric information matches the stored biometric information and whether the received local information matches the stored location information.

Abstract: An electronic device that captures a plurality of images by an image sensor. The electronic device includes control circuitry that generates a plurality of synthetic license plate images for each original license plate templates that are associated with a first hotlist of vehicles. The control circuitry generates a first augmented dataset of synthetic license plate images by an image transformation on the generated plurality of synthetic license plate images. The control circuitry trains a first neural network model using the generated first augmented dataset as a training dataset. The control circuitry detects a first vehicle in the captured plurality of images based on the extracted first license plate image portion and the trained first neural network model. The extracted first license plate image portion includes a first license plate identifier in the first hotlist of vehicles.

Abstract: Systems and methods are disclosed for assessing the quality of medical images of at least a portion of a patient's anatomy, using a computer system. One method includes receiving one or more images of at least a portion of the patient's anatomy; determining, using a processor of the computer system, one or more image properties of the received images; performing, using a processor of the computer system, anatomic localization or modeling of at least a portion of the patient's anatomy based on the received images; obtaining an identification of one or more image characteristics associated with an anatomic feature of the patient's anatomy based on the anatomic localization or modeling; and calculating, using a processor of the computer system, an image quality score based on the one or more image properties and the one or more image characteristics.

Abstract: Systems and methods for realizing practical applications of high speed digital image correlation (DIC) for dynamic quantities of interest are provided. In particular, a series of images are captured for a component of interest in which a non-filtered sensor and an analog low-pass filtered sensor are included within the region of interest for the series of images. Displacement signals are obtained for the component of interest, the non-filtered sensor, and the analog low-pass filtered sensor by applying digital image correlation processing to the series of images, which may also be wavelet filtered. Dynamic quantities of interest may be generated and derived from the displacement signals after having been wavelet filtered. Such dynamic quantities of interest based on the wavelet filtered DIC-derived displacement signal may be compared to sensor-derived dynamic quantities of interest to determine if aliasing is or is likely to be present.

Abstract: In a vehicle safety determination apparatus, an image of an area observed from a vehicle is acquired. Based on the image, a type, position, and shape of each recognition target in an image are recognized and recorded. A target is detected among recognition targets. A predicted path of the target is calculated based on recognition results of the image recognition for the recorded target. A most proximal time at which the vehicle and the target are in closest proximity is calculated based on the traveling state of the vehicle and the distance from the vehicle and the movement state of the target. A predicted position of the target at the most proximal time is calculated based on the predicted path. The safety determination regarding the target is performed based on the predicted position and on the type, position, and shape of at least one recognition target other than the target.

Abstract: Systems and methods for monitoring a user by a plurality of image sensors are disclosed. The system includes a plurality of image sensors that output content descriptive of one or more visual attributes of the user, where each of the image sensors are positioned at a unique angle facing a user. The system also includes one or more processors and one or more non-transitory memory modules communicatively coupled to the one or more processors. The non-transitory memory modules storing machine-readable instructions that, when executed, cause the one or more processors to receive the content from the plurality of image sensors, and assign respective weights to each of the plurality of image sensors based on the content. The respective weights of the plurality of image sensors are actively re-weighted over a period of time. The processors are also caused to merge the content of the plurality of image sensors together.

Abstract: A recommended object determination method includes: acquiring at least one key frame corresponding to video data, the key frame being a video frame that validly identifies an in-frame object; performing an object detection operation on a first key frame among the key frames to determine object information associated with the first key frame, the object information including: object semantic information and object visual information; and determining candidate objects based on the object semantic information, and obtaining a recommended object associated with the first key frame by screening the candidate objects based on the object visual information. A user may be provided with a object precisely associated with video content, thus improving user experience.

Abstract: A system and method of operating a vehicle. The system includes a two-dimensional imager, a three-dimensional imager, and at least one processor. The two-dimensional imager obtains a two-dimensional image of an environment surrounding the vehicle, wherein the environment includes an object. The three-dimensional imager obtains a three-dimensional (3D) point cloud of the environment. The at least one processor identifies the object from the 2D image and assigns the identification of the object to a selected point of the 3D point cloud.

Abstract: In one aspect, a request to generate an automated tour based on a set of panoramic images is received. Each particular panoramic image is associated with geographic location information and linking information linking the particular panoramic image with one or more other panoramic images in the set. A starting panoramic image and a second panoramic image are determined based at least in part on the starting panoramic image and the linking information associated with the starting and second panoramic images. A first transition between the starting panoramic image and the second panoramic image is also determined based at least in part on the linking information for these panoramic images. Additional panoramic images as well as a second transition for between the additional panoramic images are also determined. The determined panoramic images and transitions are added to the tour according to an order of the tour.

Abstract: An information processing apparatus configured to store a plurality of images captured by an imaging device, store first position information and first orientation information indicating positions and orientations of the imaging device in capturing of each of the plurality of images, identify, among from the plurality of images, a first image resembling a second image, identify a first area included in the first image, identify a second area, included in the second image, corresponding to the first area, identify second position information and second orientation information indicating a position and an orientation of the imaging device respectively in capturing of the second image, based on a comparison between a first luminance of a first pixel included in the first area and a second luminance of a second pixel included in the second area and the first position information and the first orientation information of the first image.

Abstract: For displaying a subject composition, a method determines a subject number, a subject age category, and a subject size for one or more subjects of an image. The method further calculates a subject distribution that indicates a position for a face of each subject. In addition, the method determines a subject pose for each subject that indicates a body position for the subject. The method further displays the subject composition comprising the subject distribution and the subject poses overlaying a display image.

Abstract: The present disclosure relates to the use of a hierarchical tomographic reconstruction approach that employs data representations in intermediate steps are between a full line integral and a voxel (e.g., an intermediate line integral). Each of the steps is progressively more local in nature and therefore has computational advantages and is also amenable to a deep learning solution using trained neural networks. The proposed hierarchical structure provides a mechanism to divide a large-scale inverse problem into a series of smaller-scale problems.

Abstract: Methods and systems are provided for enabling quantification and categorization of levels of user engagement of a user while wearing a head mounted display (HMD) and being presented virtual reality (VR) content. A computer-implemented method includes presenting a VR scene to an HMD user via display of the HMD and capturing one or more images of an eye of the HMD user while the HMD user is wearing the HMD and being presented with the VR scene. The method also includes operations for analyzing the one or more images for obtaining a pupil size measurement of the eye of the HMD user and for obtaining pupil size indicators usable to correlate pupil size measurements with user engagement. The method may also determine a level of user engagement based on the pupil size measurement and the pupil size indicators.

Abstract: According to examples, inventory, growth, and risk prediction using image processing may include receiving a plurality of images captured by a vehicle during movement of the vehicle along a vehicle path. The images may include a plurality of objects. The images may be pre-processed for feature extraction. A plurality of features of the objects may be extracted from the pre-processed images by using a combination of computer vision techniques. A parameter related to the objects may be determined from the extracted features. A spatial density model may be generated, based on the determined parameter and the extracted features, to provide a visual indication of density of distribution of the objects related to a portion of the images, and/or to provide an alert corresponding to the objects related to the portion of the images.

Abstract: A highlight mask is generated for an image to identify one or more highlights in the image. One or more highlight classifiers are determined for the one or more highlights in the image. One or more highlight gains are applied with the highlight mask to luminance amplitudes of pixels in the one or more highlights in the image to generate a scaled image. The one or more high-light gains for the one or more highlights are determined based at least in part on the one or more highlight classifiers determined for the one or more highlights.