Abstract: An indoor positioning system and method are provided. The indoor positioning method includes: establishing an image database through a BIM model of a target area, and using a trained deep learning model to extract features of a virtual image; after obtaining a captured image in the target area, using the trained deep learning model to extract features thereof, and performing similarity matching with the image database to calculate a spatial position of a most similar image; calculating the most similar image and its essential matrix through multiple sets of feature points, and obtaining capturing positions and capturing pose parameters as positioning results; projecting the BIM model to a tracking captured image, and updating the positioning results and the capturing pose parameters with a visual inertial odometer; and continuously correcting the positioning results and the capturing pose parameters by detecting horizontal and vertical planes from the tracking captured image.

Abstract: The method of generating three-dimensional model data of an object includes estimating pose data of the object based on the first view data of the camera and first relative pose data of the object, and estimating second relative pose data of the object based on the pose data of the object and the second view data of the camera.

Abstract: A system (300) includes a memory (324) configured to store an inflammation map generator module (328). The system further includes a processor (322) configured to: receive at least one of spectral projection data or spectral volumetric image data, decompose the at least one of spectral projection data or spectral volumetric image data using a two-basis decomposition to generate a set of vectors for each basis represented in the at least one of spectral projection data or spectral volumetric image data, compute a concentration of each basis within a voxel from the set of vectors for each basis, and determine a concentration of at least one of fat or inflammation within the voxel from the concentration of each basis. The system further includes a display configured to display the determined concentration of the at least one of fat or inflammation.

Abstract: Methods and systems are disclosed for performing operations comprising: receiving an image that includes a depiction of a face of a user; generating a plurality of landmarks of the face based on the received image; removing a set of interfering landmarks from the plurality of landmarks resulting in a remaining set of landmarks of the plurality of landmarks; obtaining a depth map for the face of the user; and computing a real-world scale of the face of the user based on the depth map and the remaining set of landmarks.

Abstract: According to at least one aspect, a system for scanning an object is provided. The system comprises at least one hardware processor; and at least one non-transitory computer-readable storage medium storing processor executable instructions that, when executed by the at least one hardware processor, cause the at least one hardware processor to perform: generating a first 3-dimensional (3D) model of the object; identifying a set of imaging positions from which to capture at least one image based on the first 3D model of the object; obtaining a set of images of the object captured at, or approximately at, the set of imaging positions; and generating a second 3D model of the object based on the set of images.

Abstract: A ship information display device is provided, which may include a first processor, a second processor, a graphic processor, and a display. The first processor may generate a first image based on first ship information received from a first ship sensor and generate a screen to be synthesized including the first image and a blank image. The second processor may generate a second image based on second ship information received from a second ship sensor. The graphic processor may generate a synthesized screen including the first image and the second image by replacing the blank image of the screen to be synthesized by the second image generated by the second processor. The display may display the synthesized screen.

Abstract: The present disclosure provides an image processing method and apparatus, an electronic device, and a computer-readable storage medium.

Abstract: In one example embodiment, a software application obtains a set of images that include an aerial cable and generates a 3D model from the set of images. The 3D model initially excludes a representation of the aerial cable. The software application processes each image of the set of images to extract pixels that potentially represent cables and determines a position in 3D space of the 3D model of a pair of attachment points for the aerial cable. The software application defines a vertical plane in 3D space of the 3D model based on the pair of cable attachment points. For each of one or more images of the set of images, the software application projects at least some of the pixels that potentially represent cables onto the vertical plane. The software application then calculates a curve representation (e.g., a catenary equation) for the aerial cable based on the pixels projected onto the vertical plane, and adds a cable model defined by the curve representation to the 3D model to represent the aerial cable.

Abstract: The disclosure provides methods and systems for automatically generating an animatable object, such as a 3D model. In particular, the present technology provides fast, easy, and automatic animatable solutions based on unique facial characteristics of user input. Various embodiments of the present technology include receiving user input, such as a two-dimensional image or three-dimensional scan of a user's face, and automatically detecting one or more features. The methods and systems may further include deforming a template geometry and a template control structure based on the one or more detected features to automatically generate a custom geometry and custom control structure, respectively. A texture of the received user input may also be transferred to the custom geometry. The animatable object therefore includes the custom geometry, the transferred texture, and the custom control structure, which follow a morphology of the face.

Abstract: A method is provided for modifying an image. The method comprises displaying an image, the image comprising a portion of an object; and determining if an edge of the object is in a location within the portion. The method further comprises detecting movement, in a member direction, of an operating member with respect to the edge. The method still further comprises moving, if the edge is not in the location, the object in an object direction corresponding to the detected movement; and modifying, if the edge is in the location, the image in response to the detected movement, the modified image comprising the edge in the location.

Abstract: The present invention provides a system and method of automatic detection of structure integrity threats. A threat detection engine detects integrity threats in structures, such as underwater structures, and segments the structures in an image using convolutional neural networks (“CNN”). The threat detection engine may include a dataset module, a CNN training module, a segmentation map module, a semi-supervision module, and an efficiency module. The threat detection engine may train a deep learning model to detect anomalies in videos. To do so, a dataset module with videos may be used where the dataset module includes annotations detailing at what timestamps one or more anomalies are visible.

Abstract: A processor may receive physical parameter data associated with a physical parameter of an object. The processor may receive pathway data associated with one or more potential pathways for transporting the object from an origin point to a destination point. The processor may determine a recommended pathway, the recommended pathway may have one or more path segments for transportation of the object from the origin point to the destination point. The processor may determine a first recommended orientation and a first recommended movement for transportation of the object through a first path segment of the recommended path. The processor may provide, to a user, a virtual rendering of the first recommended orientation and the first recommended movement of the object through the first path segment of the recommended path.

Abstract: An animation system wherein a machine learning model is adopted to generate animated facial actions based on parameters obtained from a live actor. Specifically, the anatomical structure such as a facial muscle topology and a skull surface that are specific to the live actor may be used. A skull surface that is specific to a live actor based on facial scans of the live actor and generic tissue depth data. For example, the facial scans of the live actor may provide a skin surface topology of the live actor, based on which the skull surface underneath the skin surface can be derived by “offsetting” the skin surface with corresponding soft tissue depth at different sampled points on the skin surface.

Abstract: A position posture identification device includes: an actual measurement data acquisition unit which acquires actual measurement data on the shape of a workpiece; a virtual measurement data generation unit which generates, from shape data defined for the workpiece, virtual measurement data; a filter processing unit which performs, based on the measurement property of the three-dimensional measuring machine, affine transformation on the virtual measurement data; a feature point extraction unit which extracts feature point data from the actual measurement data and the virtual measurement data; a storage unit which stores, as model data of the workpiece, the feature point data extracted from the virtual measurement data; and a position posture calculation unit which checks the feature point data of the actual measurement data against data obtained by performing coordinate transformation on the feature point data included in the model data so as to calculate the position posture of the workpiece.

Abstract: Methods and apparatuses for tracking objects comprise one or more optical sensors for capturing one or more images of a scene, wherein the one or more optical sensors capture a wide field of view and corresponding narrow field of view for the one or more images of a scene, a localization module, coupled to the one or more optical sensors for determining the location of the apparatus, and determining the location of one more objects in the one or more images based on the location of the apparatus and an augmented reality module, coupled to the localization module, for enhancing a view of the scene on a display based on the determined location of the one or more objects.

Abstract: Disclosed are methods, systems, and articles of manufacture for managing and displaying web pages and web resources in a virtual three-dimensional (3D) space with an extended reality system. These techniques receive an input for 3D transform for a web page or a web page panel therefor. In response to the input, a browser engine coupled to a processor of an extended reality system determines 3D transform data for the web page or the web page panel based at least in part upon the 3D transform of the web page or the web page panel, wherein the 3D transform comprises a change in 3D position, rotation, or scale of the web page or the web page panel therefor in a virtual 3D space. A universe browser engine may present contents of the web page in a virtual 3D space based at least in part upon the 3D transform data.

Abstract: Systems and techniques are provided for facial image augmentation. An example method can include obtaining a first image capturing a face. Using the first image, the method can determine, using a prediction model, a UV face position map including a two-dimensional (2D) representation of a three-dimensional (3D) structure of the face. The method can generate, based on the UV face position map, a 3D model of the face. The method can generate an extended 3D model of the face by extending the 3D model to include region(s) beyond a boundary of the 3D model. The region(s) can include a forehead region, a region surrounding at least a portion of the face, and/or other region. The method can generate, based on the extended 3D model, a second image depicting the face in a rotated position relative to a position of the face in the first image.

Abstract: In an example, a method can include segmented image volume data for at least one anatomic structure, wherein the segmented image volume data includes a 3-D image volume that includes the at least one anatomic structure. The method can include searching outward from a computed centerline for the at least one anatomic structure to detect a surface of one or more regions of interest of the at least one anatomic structure by evaluating values associated with voxels representing the 3-D image volume that includes the at least one anatomic structure relative to a threshold. The method can further include isolating the one or more regions of interest of the at least one anatomic structure in response to the searching and generating a region of interest model based on the one or more isolated regions of interest.

Abstract: A method of aligning a digital model of a structure with a displayed portion of the structure within a video stream is disclosed. An approximate position of the camera device in the digital model is determined. A position and an orientation are determined for a plurality of digital surfaces within the digital model visible from the approximate position of the camera device. A position and an orientation of a plurality of object surfaces visible in a video stream are determined. A 3D translation, a 3D scale, and a 3D rotation that maximize an alignment of the position and orientation of the plurality of digital surfaces with the position and orientation of the plurality of object surfaces are determined. The 3D translation, the 3D scale, and the 3D rotation are applied to the digital model and the digital model is displayed contemporaneously with a display of the video stream.

Abstract: Techniques and systems are provided for determining features of one or more objects in one or more images. For example, an image of an object and a three-dimensional model associated with the object can be obtained. From the image, a sample point on the object can be determined. A depth and an angle of the sample point of the object can be determined. A pose and a shape of the three-dimensional model associated with the object can be determined based on the depth and the angle.