Abstract: Examples are disclosed that relate to a camera model for a machine vision application. One example provides instructions executable to receive image data obtained by an image sensor of a camera, the image data capturing a calibration pattern comprising a plurality of calibration features, for each of one or more imaged calibration features in the image data, determine an object space location of the imaged calibration feature, and determine a distance between the object space location and a corresponding ray of a camera model, the camera model defining a plurality of rays that each represent a relationship of an image space location on the image sensor to object space. The instructions are further executable to determine a value of a cost function based on the distances, adjust the camera model until the cost function meets a target condition, and use the camera model in a machine vision application.

Abstract: One disclosed example provides a head-mounted device configured to control a plurality of light sources of a handheld object and acquire image data comprising a sequence of environmental tracking exposures in which the plurality of light sources are controlled to have a lower integrated intensity and handheld object tracking exposures in which the plurality of light sources are controlled to have a higher integrated intensity. The instructions are further executable to detect, via an environmental tracking exposure, one or more features of the surrounding environment, determine a pose of the head-mounted device based upon the one or more features of the surrounding environment detected, detect via a handheld object tracking exposure the plurality of light sources of the handheld object, determine a pose of the handheld object relative to the head-mounted device based upon the plurality of light sources detected, and output the pose of the handheld object.

Abstract: One disclosed example provides a head-mounted device configured to control a plurality of light sources of a handheld object and acquire image data comprising a sequence of environmental tracking exposures in which the plurality of light sources are controlled to have a lower integrated intensity and handheld object tracking exposures in which the plurality of light sources are controlled to have a higher integrated intensity. The instructions are further executable to detect, via an environmental tracking exposure, one or more features of the surrounding environment, determine a pose of the head-mounted device based upon the one or more features of the surrounding environment detected, detect via a handheld object tracking exposure the plurality of light sources of the handheld object, determine a pose of the handheld object relative to the head-mounted device based upon the plurality of light sources detected, and output the pose of the handheld object.

Abstract: One disclosed example provides a head-mounted device configured to control a plurality of light sources of a handheld object and acquire image data comprising a sequence of environmental tracking exposures in which the plurality of light sources are controlled to have a lower integrated intensity and handheld object tracking exposures in which the plurality of light sources are controlled to have a higher integrated intensity. The instructions are further executable to detect, via an environmental tracking exposure, one or more features of the surrounding environment, determine a pose of the head-mounted device based upon the one or more features of the surrounding environment detected, detect via a handheld object tracking exposure the plurality of light sources of the handheld object, determine a pose of the handheld object relative to the head-mounted device based upon the plurality of light sources detected, and output the pose of the handheld object.

Abstract: One disclosed example provides a computing device configured to receive from an image sensor of a head-mounted device environmental tracking exposures and handheld object tracking exposures, determine a pose of the handheld object with respect to the head-mounted device based upon the handheld object tracking exposures, determine a pose of the head-mounted device with respect to a surrounding environment based upon the environmental tracking exposures, derive a pose of the handheld object relative to the surrounding environment based upon the pose of the handheld object with respect to the head-mounted device and the pose of the head-mounted device with respect to the surrounding environment, and output the pose of the handheld object relative to the surrounding environment for controlling a user interface displayed on the head-mounted device.

Abstract: Examples are disclosed that relate to a camera model for a machine vision application. One example provides instructions executable to receive image data obtained by an image sensor of a camera, the image data capturing a calibration pattern comprising a plurality of calibration features, for each of one or more imaged calibration features in the image data, determine an object space location of the imaged calibration feature, and determine a distance between the object space location and a corresponding ray of a camera model, the camera model defining a plurality of rays that each represent a relationship of an image space location on the image sensor to object space. The instructions are further executable to determine a value of a cost function based on the distances, adjust the camera model until the cost function meets a target condition, and use the camera model in a machine vision application.

Abstract: Examples are disclosed herein that relate to determining a pose of a handheld object. One example provides a computing system configured to determine a pose of a handheld object comprising a plurality of light sources by acquiring image data of a surrounding environment, detecting a subset of light sources of the plurality of light sources of the handheld object in the image data, and performing a search, without using previous pose data, to determine the pose of the handheld object relative to the computing system. The computing system is further configured to use the pose determined to perform a later search for an updated pose of the handheld object, and if the later search fails to find the updated pose, determine the updated pose by again performing the search without using previous pose data.

Abstract: One disclosed example provides a head-mounted device including a stereo camera arrangement, a logic device configured to execute instructions, and a storage device storing instructions executable by the logic device to, for each camera in the stereo camera arrangement, receive image data of a field of view of the camera, detect light sources of a handheld object in the image data, and based upon the light sources detected, determine a pose of the handheld object. The instructions are executable to, based upon the pose of the handheld object determined for each camera in the stereo camera arrangement, calibrate the stereo camera arrangement.

Abstract: Examples are disclosed herein that relate to determining a pose of a handheld object. One example provides a computing system configured to determine a pose of a handheld object comprising a plurality of light sources by acquiring image data of a surrounding environment, detecting a subset of light sources of the plurality of light sources of the handheld object in the image data, and performing a search, without using previous pose data, to determine the pose of the handheld object relative to the computing system. The computing system is further configured to use the pose determined to perform a later search for an updated pose of the handheld object, and if the later search fails to find the updated pose, determine the updated pose by again performing the search without using previous pose data.

Abstract: One disclosed example provides a computing device configured to receive from an image sensor of a head-mounted device environmental tracking exposures and handheld object tracking exposures, determine a pose of the handheld object with respect to the head-mounted device based upon the handheld object tracking exposures, determine a pose of the head-mounted device with respect to a surrounding environment based upon the environmental tracking exposures, derive a pose of the handheld object relative to the surrounding environment based upon the pose of the handheld object with respect to the head-mounted device and the pose of the head-mounted device with respect to the surrounding environment, and output the pose of the handheld object relative to the surrounding environment for controlling a user interface displayed on the head-mounted device.

Abstract: One disclosed example provides a head-mounted device including a stereo camera arrangement, a logic device configured to execute instructions, and a storage device storing instructions executable by the logic device to, for each camera in the stereo camera arrangement, receive image data of a field of view of the camera, detect light sources of a handheld object in the image data, and based upon the light sources detected, determine a pose of the handheld object. The instructions are executable to, based upon the pose of the handheld object determined for each camera in the stereo camera arrangement, calibrate the stereo camera arrangement.

Abstract: One disclosed example provides a head-mounted device configured to control a plurality of light sources of a handheld object and acquire image data comprising a sequence of environmental tracking exposures in which the plurality of light sources are controlled to have a lower integrated intensity and handheld object tracking exposures in which the plurality of light sources are controlled to have a higher integrated intensity. The instructions are further executable to detect, via an environmental tracking exposure, one or more features of the surrounding environment, determine a pose of the head-mounted device based upon the one or more features of the surrounding environment detected, detect via a handheld object tracking exposure the plurality of light sources of the handheld object, determine a pose of the handheld object relative to the head-mounted device based upon the plurality of light sources detected, and output the pose of the handheld object.

Abstract: A pattern matching engine and associated method for detecting one or more of headers, footers, watermarks, page numbering, page colors, and page borders appearing in a fixed format document. The pattern matching engine performs pattern matching across pages of the fixed format document to identify repeating patterns. Using heuristic analysis, repeating patterns meeting selected criteria are classified as headers, footers, or watermarks. Filtering removes repeating patterns unlikely to represent headers, footers, or watermarks. The information produced by the pattern matching engine allows the repeating elements to be properly reconstructed as flowable elements when converting a fixed format document into a flow format document.