Abstract: In one embodiment, a method includes receiving sensor data of a scene captured using one or more sensors, generating (1) a number of virtual surfaces representing a number of detected planar surfaces in the scene and (2) a point cloud representing detected features of objects in the scene based on the sensor data, assigning each point in the point cloud to one or more of the number of virtual surfaces, generating occupancy volumes for each of the number of virtual surfaces based on the points assigned to the virtual surface, generating a datastore including the number of virtual surfaces, the occupancy volumes of each of the number of virtual surfaces, and a spatial relationship between the number of virtual surfaces, receiving a query, and sending a response to the query, the response including an identified subset of the plurality of virtual surfaces in the datastore that satisfy the query.

Abstract: A method of interacting with an artificial-reality (AR) content at an AR headset that includes cameras and displays is described. The method includes, while the AR headset has a first position within a physical environment that includes an object, if a distance of the object is within a threshold collision distance from the AR headset, presenting a meshed representation of the object. The meshed representation is displayed at first respective locations on the displays such that the meshed representation is viewable within the artificial reality. After the AR headset moves to a second position with a different distance, and if the different distance is within the threshold collision distance from the AR headset, moving the meshed representation of the object to second respective locations within the artificial reality. The second respective locations correspond to the position of the object in the physical environment.

Abstract: In an attachment attaching/detaching device 2, a fixed hook 22 that engages a first pin 51 of an attachment 5, and a movable hook 23 that moves toward and away from the fixed hook 22 and engages a second pin 52 of the attachment 5 are provided in an arm connection part 21 to which an arm 12 and a rod or a link 15 are connected. A tilt switch 46 that switches between allowing a flow of current and cutting off a flow of current depending on a tilted posture is mounted to the arm connection part 21 in a state in which the tilt switch 46 is interposed along a shared power supply line 283 to electric driving means for causing the movable hook 23 to advance and retreat. Thus, safety securing means that replaces a locking mechanism is realized.

Abstract: A method of interacting with an artificial-reality (AR) content at an AR headset that includes cameras and displays is described. The method includes, while the AR headset has a first position within a physical environment that includes an object, if a distance of the object is within a threshold collision distance from the AR headset, presenting a meshed representation of the object. The meshed representation is displayed at first respective locations on the displays such that the meshed representation is viewable within the artificial reality. After the AR headset moves to a second position with a different distance, and if the different distance is within the threshold collision distance from the AR headset, moving the meshed representation of the object to second respective locations within the artificial reality. The second respective locations correspond to the position of the object in the physical environment.

Abstract: Implementations described herein can share scene data between multiple artificial reality (XR) devices, such as head-mounted displays (HMDs). A first XR device can retrieve stored spatial anchors associated with a scene, and align a coordinate frame with coordinate frames for a second XR device using the spatial anchors. The second XR device can have identified physical objects in the scene with corresponding object types defined in a scene lexicon (e.g., with a camera on the second XR device capturing images of physical objects and performing object recognition or through manual tagging of objects with object types), and store the object types and locations of the physical objects as scene data. The first XR device can obtain the scene data based on associations between the scene data and the spatial anchors and render virtual objects using the scene data, without having to rescan the scene for the physical objects.

Abstract: In one embodiment, a method includes receiving sensor data of a scene captured using one or more sensors, generating (1) a number of virtual surfaces representing a number of detected planar surfaces in the scene and (2) a point cloud representing detected features of objects in the scene based on the sensor data, assigning each point in the point cloud to one or more of the number of virtual surfaces, generating occupancy volumes for each of the number of virtual surfaces based on the points assigned to the virtual surface, generating a datastore including the number of virtual surfaces, the occupancy volumes of each of the number of virtual surfaces, and a spatial relationship between the number of virtual surfaces, receiving a query, and sending a response to the query, the response including an identified subset of the plurality of virtual surfaces in the datastore that satisfy the query.

Abstract: In one embodiment, a method includes receiving sensor data of a scene captured using one or more sensors, generating (1) a number of virtual surfaces representing a number of detected planar surfaces in the scene and (2) a point cloud representing detected features of objects in the scene based on the sensor data, assigning each point in the point cloud to one or more of the number of virtual surfaces, generating occupancy volumes for each of the number of virtual surfaces based on the points assigned to the virtual surface, generating a datastore including the number of virtual surfaces, the occupancy volumes of each of the number of virtual surfaces, and a spatial relationship between the number of virtual surfaces, receiving a query, and sending a response to the query, the response including an identified subset of the plurality of virtual surfaces in the datastore that satisfy the query.

Abstract: In some implementations, the disclosed systems and methods can replace components descriptive of private real-world objects with generic components that obscure details of the private real-world objects, such as the objects' structure and semantic information. In some implementations, the disclosed systems and methods can convert image and/or sensor data into pose data that can be used by a recipient device to animate an avatar of the sender while the audio stream is being played.

Abstract: A method of interacting with an artificial-reality (AR) content at an AR headset that includes cameras and displays is described. The method includes, while the AR headset has a first position within a physical environment that includes an object, if a distance of the object is within a threshold collision distance from the AR headset, presenting a meshed representation of the object. The meshed representation is displayed at first respective locations on the displays such that the meshed representation is viewable within the artificial reality. After the AR headset moves to a second position with a different distance, and if the different distance is within the threshold collision distance from the AR headset, moving the meshed representation of the object to second respective locations within the artificial reality. The second respective locations correspond to the position of the object in the physical environment.

Abstract: A method of interacting with an artificial-reality (AR) content at an AR headset that includes cameras and displays is described. The method includes, while the AR headset has a first position within a physical environment that includes an object, if a distance of the object is within a threshold collision distance from the AR headset, presenting a meshed representation of the object. The meshed representation is displayed at first respective locations on the displays such that the meshed representation is viewable within the artificial reality. After the AR headset moves to a second position with a different distance, and if the different distance is within the threshold collision distance from the AR headset, moving the meshed representation of the object to second respective locations within the artificial reality. The second respective locations correspond to the position of the object in the physical environment.

Abstract: The data analysis server manages first data configuration information for managing a correspondence of the learned data model, a raw data bucket that stores the raw data for generating the learned data model, and a curated data bucket that stores the curated data for generating the learned data model and second data configuration information for managing correspondences of the learned data model and the first storage area, the curated data bucket and the second storage area, and the raw data bucket and the third storage area, and gives an instruction to acquire snapshots of the second storage area that stores the curated data for generating the learned data model and the third storage area that stores the raw data for generating the learned data model to the data storage via the storage management server when the learned data model is generated.

Abstract: In one embodiment, a method includes receiving sensor data of a scene captured using one or more sensors, generating (1) a number of virtual surfaces representing a number of detected planar surfaces in the scene and (2) a point cloud representing detected features of objects in the scene based on the sensor data, assigning each point in the point cloud to one or more of the number of virtual surfaces, generating occupancy volumes for each of the number of virtual surfaces based on the points assigned to the virtual surface, generating a datastore including the number of virtual surfaces, the occupancy volumes of each of the number of virtual surfaces, and a spatial relationship between the number of virtual surfaces, receiving a query, and sending a response to the query, the response including an identified subset of the plurality of virtual surfaces in the datastore that satisfy the query.

Abstract: In one embodiment, a method includes receiving sensor data of a scene captured using one or more sensors, generating (1) a number of virtual surfaces representing a number of detected planar surfaces in the scene and (2) a point cloud representing detected features of objects in the scene based on the sensor data, assigning each point in the point cloud to one or more of the number of virtual surfaces, generating occupancy volumes for each of the number of virtual surfaces based on the points assigned to the virtual surface, generating a datastore including the number of virtual surfaces, the occupancy volumes of each of the number of virtual surfaces, and a spatial relationship between the number of virtual surfaces, receiving a query, and sending a response to the query, the response including an identified subset of the plurality of virtual surfaces in the datastore that satisfy the query.

Abstract: Provided is a data management method capable of deleting intermediate data at an appropriate timing. The data management method in a data analysis system that performs analysis by combining a plurality of input data based on an analysis execution request from a computer includes: a first step, in which a request analysis unit analyzes the analysis execution request from the computer to identify a task, identifies intermediate data generated after execution of each identified task, and generates constraint information that determines whether to delete the identified intermediate data; a second step, in which a task management unit determines whether to delete the intermediate data based on the constraint information for each identified task; and a third step, in which a task execution unit executes the identified task and deletes the intermediate data of the task based on a determination result of the second step.

Abstract: A method for machining a workpiece by a numerical control (NC) machine constructs a model of a scene from one or multiple images including at least a part of the workpiece and a part of the NC machine and registers a model of the NC machine with the model of the scene to produce a first transformation between a coordinate system of the model of the scene and a coordinate system of the NC machine. The method also detects the workpiece in the model of the scene to produce a second transformation between the coordinate system of the model of the scene and a coordinate system of the workpiece and combines the first and the second transformations to register the coordinate system of the workpiece with the coordinate system of the NC machine. The registered workpiece is machined with a tool of the NC machine.

Abstract: A method calibrates one or more cameras, wherein the one or more cameras acquire images of a scene for different viewpoints, and wherein the images are non-overlapping, by first constructing a 3D model of the scene using a calibration camera that is independent of the one or more cameras, and a simultaneous localization and mapping (SLAM) procedure. 2D-to-3D correspondences between each of the images and the 3D model are determined. Then, calibration parameters of each of the one or more cameras are estimated using a 2D-to-3D registration procedure.

Abstract: The data analysis server manages first data configuration information for managing a correspondence of the learned data model, a raw data bucket that stores the raw data for generating the learned data model, and a curated data bucket that stores the curated data for generating the learned data model and second data configuration information for managing correspondences of the learned data model and the first storage area, the curated data bucket and the second storage area, and the raw data bucket and the third storage area, and gives an instruction to acquire snapshots of the second storage area that stores the curated data for generating the learned data model and the third storage area that stores the raw data for generating the learned data model to the data storage via the storage management server when the learned data model is generated.

Abstract: Provided is an elevator shaft dimensions measurement device including: a plurality of 3-D distance image sensors which are arranged on a circumference of the same circle, facing the direction of the center of the circle and inclined at an elevation angle with respect to a horizontal plane, and which output measurement data by capturing an image of a pattern irradiated onto the inner walls of an elevator shaft that are imaging objects; and a computer which integrates the measurement data output from the plurality of 3-D distance image sensors at a plurality of height positions in the elevator shaft, generates first integrated measurement data covering 360 degrees in the horizontal direction, aligns the first integrated measurement data to create second integrated measurement data after the alignment, and calculates the dimensions of the elevator shaft on the basis of the second integrated measurement data after the alignment.

Abstract: A method and system detects and localizes multiple instances of an object by first acquiring a frame of a three-dimensional (3D) scene with a sensor, and extracting features from the frame. The features are matched according to appearance similarity and triplets are formed among matching features. Based on 3D locations of the corresponding points in the matching triplets, a geometric transformation is computed. Matching triplets are clustered according to the computed geometric transformations. Since the set of features coining from two different object instances should have a single geometric transform, the output of clustering provides the features and poses of each object instance in the image.

Abstract: An imaging system for localization and mapping of a scene including static and dynamic objects. A sensor acquires a sequence of frames in motion or stationary. A memory to store a static map of static objects and an object map of each dynamic object in the scene. The static map includes a set of landmarks, and the object map includes a set of landmarks and a set of segments. A localizer registers keypoints of the frame with landmarks in the static map using frame-based registration and to register some segments in the frame with segments in the object map using a segment-based registration. A mapper to update each object map with keypoints forming each segment and keypoints registered with the corresponding object map according to the segment-based registration, and to update the static map with the remaining keypoints in the frame using the keypoints registered with the static map.