A head mounted display device is provided that includes a display device, a camera device, an input device, and a processor. The processor is configured to store a database of physical objects and virtual objects that have been associated with one or more semantic tags. The processor is further configured to receive a natural language input from a user via the input device and perform semantic processing on the natural language input to determine a user specified operation and identify one or more semantic tags indicated by the natural language input. The processor is further configured to select a target virtual object and a target physical object based on the identified one or more semantic tags, perform the determined user specified operation on the target virtual object based on the target physical object, and display the target virtual object at a physical location associated with the target physical object.

A method of generating log data that includes a plurality of records, in which information detected through image recognition processing on a plurality of image frames is recorded. The method includes, detecting objects in each image frame through the image recognition processing, generating a record including identification information of each image frame and the aggregated number of objects detected in the image frame for each image frame, and adding metadata relating to the detected objects to the corresponding record when the aggregated number of objects is equal to or greater than one. When the aggregated number of objects is zero, the metadata related to the detected objects is not added to the record.

A structure damage cause estimation system, a structure damage cause estimation method, and a structure damage cause estimation server that enable a damage cause to be estimated with a high probability are provided. A structure damage cause estimation system (100) includes a database (110) that has data of a captured image and a damage cause of a structure, an image acquisition unit (115) that acquires a captured image of a target structure to be inspected, a damage detection unit (125) that detects damage from the captured image, a similar damage extraction unit (130) that extracts similar damage similar to the damage by using the database (110), and a damage cause presentation unit (135) that presents damage causes of the similar damage. Also provided are a damage cause estimation method that uses the structure damage cause estimation system (100), and a damage cause estimation server.

A structure repair method selection system includes a repair evaluation unit that obtains an evaluation score for a structure after repair, a database that has data of a captured image of the structure and the evaluation score, an image acquisition unit that acquires a captured image of a target structure to be repaired, a damage detection unit that detects damage from the captured image, a similar damage extraction unit that extracts similar damage similar to the damage by using the database, and a repair method presentation unit that presents, based on the evaluation score, repair methods used for the similar damage. Also provided are a repair method selection method that uses the structure repair method selection system, and a repair method selection server.

In an embodiment, a method of emulating light sensitivity of a target includes, for each of at least some frames of a video recording, receiving an image. The method also includes accessing image metadata associated with the image. The method also includes discovering, from the image metadata, information related to an exposure setting and a gain value used by a camera in capture of the image. The method also includes deriving, from stored camera metadata for the camera, information related to a luminous flux associated with the exposure setting and the gain value used by the camera in the capture of the image. The method also includes determining an adjusted gain value corresponding to a target light sensitivity using the derived information related to the luminous flux. The method also includes generating an adjusted image using the adjusted gain value.

In an embodiment, a method of emulating light sensitivity of a target includes, for each of at least some frames of a video recording, receiving an image. The method also includes accessing image metadata associated with the image. The method also includes discovering, from the image metadata, information related to an exposure setting and a gain value used by a camera in capture of the image. The method also includes deriving, from stored camera metadata for the camera, information related to a luminous flux associated with the exposure setting and the gain value used by the camera in the capture of the image. The method also includes determining an adjusted gain value corresponding to a target light sensitivity using the derived information related to the luminous flux. The method also includes generating an adjusted image using the adjusted gain value.

A method for detecting obstacles, the method may include receiving, from a plurality of vehicles, and by an I/O module of a computerized system, visual information acquired during executions of vehicle maneuvers that are suspected as being obstacle avoidance maneuvers; determining, based at least on the visual information, at least one visual obstacle identifier for visually identifying at least one obstacle; and transmitting to one or more of the plurality of vehicles, the at least one visual obstacle identifier.

A method for detecting obstacles, the method may include receiving, from a plurality of vehicles, and by an I/O module of a computerized system, visual information acquired during executions of vehicle maneuvers that are suspected as being obstacle avoidance maneuvers; determining, based at least on the visual information, at least one visual obstacle identifier for visually identifying at least one obstacle; and transmitting to one or more of the plurality of vehicles, the at least one visual obstacle identifier.

Provided are an ink data generation apparatus, an ink data generation method, and an ink data generation program that are capable of improving ease of handling ink data when or after metadata is generated. An ink data generation apparatus performs a determination as to an inclusion relation between a first set and a second set by comparing stroke elements of first set data and stroke elements of second set data using the first set data and the second set data. The ink data generation apparatus generates first metadata for the first set described in a form that varies in accordance with a result of the determination.

An approach is provided in which the approach the approach deconstructs a user interface into user interface elements that each are assigned an importance score. The approach compares a user eye gaze pattern of a user viewing the user interface against an expected eye gaze pattern corresponding to the user interface, and determines that the user requires assistance navigating the user interface. The approach selects one of the user interface elements based on its importance score, generates an augmented reality overlay of the selected user interface element, and displays the augmented reality overlay on the user interface using an augmented reality device.