Abstract: Methods for augmentation of previously captured augmented reality data with subsequently captured data are disclosed. A subsequent capture of a scene and associated AR data, such as a point cloud, may be correlated with the previously captured data by various methods, including image matching, object recognition, and geolocation referencing. Following correlation, the previously captured data may be augmented by the AR data from the subsequent capture, which may include adding or deleting points. Some existing points may be modified in some aspects where a subsequent capture includes more reliable data.

Abstract: A platform for synchronizing augmented reality (AR) views and information between two or more network connected devices is disclosed. A first device captures a video stream and associated spatial information, and transmits the video stream and spatial information to a second device. A user of the second device views the video stream, and inserts one or more AR objects into the video stream, with reference to the spatial information. The second device transmits the AR objects and spatial information references to the first device, which then renders the one or more AR objects into the video stream, using the spatial information references to locate the AR objects in each video stream frame.

Abstract: Methods and systems for the remote delivery of professional services, using augmented reality (AR), are disclosed. In embodiments, a user transmits an image or video to a server, which provides a list of professionals on the basis of object recognition performed on the image or video. The user selects a professional, and the server initiates a video session between a user device and a professional device, where the professional can superimpose one or more AR objects on the video, to be displayed on the user device.

Abstract: Methods and systems for automatic detection and recognition of visual tags on equipment are disclosed. The make and model of an object such as an appliance or consumer device is recognized from an image or video using object detection. This make and model information may then be used to direct a user to locate an equipment information tag that includes model and serial number information. Object recognition and optical character recognition can then be employed to extract the model and serial number from the tag, along with any other relevant information. The extracted information may then be used to locate service and/or operation information.

Abstract: Methods for placement of location-persistent 3D objects or annotations in an augmented reality scene are disclosed. By capturing location data along with device spatial orientation and the placement of 3D objects or annotations, the augmented reality scene can be recreated and manipulated. Placed 3D objects or annotations can reappear in a subsequent capture by the same or a different device when brought back to the location of the initial capture and placement of objects. Still further, the placed 3D objects or annotations may be supplemented with additional objects or annotations, or the placed objects or annotations may be removed or modified.

Abstract: Methods for replacing or obscuring objects detected in an image or video on the basis of image context are disclosed. Context of the image or video may be obtained via pattern recognition on audio associated with the image or video, by user-supplied context, and/or by context derived from image capture, such as the nature of an application used to capture the image. The image or video may be analyzed for object detection and recognition, and depending upon policy, the image or video context used to select objects related or unrelated to the context for replacement or obfuscation. The selected objects may then be replaced with generic objects rendered from 3D models, or blurred or otherwise obscured.

Abstract: Methods for improving object recognition using depth data are disclosed. An image is captured of a 3-D scene along with depth data, such as in the form of a point cloud. The depth data is correlated with the image of the captured scene, such as by determining the frame of reference of each of the image and the depth data, thereby allowing the depth data to be mapped to the correct corresponding pixels of the image. Object recognition on the image is then improved by employing the correlated depth data. The depth data may be captured contemporaneously with the image of the 3-D scene, such as by using photogrammetry, or at a different time.

Abstract: Methods for automatically tagging one or more images and/or video clips using a audio stream are disclosed. The audio stream may be processed using an automatic speech recognition algorithm, to extract possible keywords. The image(s) and/or video clip(s) may then be tagged with the possible keywords. In some embodiments, the image(s) and/or video clip(s) may be tagged automatically. In other embodiments, a user may be presented with a list of possible keywords extracted from the audio stream, from which the user may then select to manually tag the image(s) and/or video clip(s).

Abstract: Methods for augmentation of previously captured augmented reality data with subsequently captured data are disclosed. A subsequent capture of a scene and associated AR data, such as a point cloud, may be correlated with the previously captured data by various methods, including image matching, object recognition, and geolocation referencing. Following correlation, the previously captured data may be augmented by the AR data from the subsequent capture, which may include adding or deleting points. Some existing points may be modified in some aspects where a subsequent capture includes more reliable data.

Abstract: A platform for synchronizing augmented reality (AR) views and information between two or more network connected devices is disclosed. A first device captures a video stream and associated spatial information, and transmits the video stream and spatial information to a second device. A user of the second device views the video stream, and inserts one or more AR objects into the video stream, with reference to the spatial information. The second device transmits the AR objects and spatial information references to the first device, which then renders the one or more AR objects into the video stream, using the spatial information references to locate the AR objects in each video stream frame.

Abstract: A method for creating and storing a captured image and associated spatial data and augmented reality (AR) data in a file that allows subsequent manipulation and processing of AR objects is disclosed. In embodiments, one or more frames are extracted from a video stream, along with spatial information about the camera capturing the video stream. The one or more frames are analyzed in conjunction with the spatial information to calculate a point cloud of depth data. The one or more frames are stored in a file in a first layer, and the point cloud is stored in the file in a second layer. In some embodiments, one or more AR objects are stored in a third layer.

Abstract: Methods and systems for the remote delivery of professional services, using augmented reality (AR), are disclosed. In embodiments, a user transmits an image or video to a server, which provides a list of professionals on the basis of object recognition performed on the image or video. The user selects a professional, and the server initiates a video session between a user device and a professional device, where the professional can superimpose one or more AR objects on the video, to be displayed on the user device.