Abstract: Systems and methods are described herein to generate a 3D surface scan of a surface profile of a patient's anatomy. The 3D surface scan may be generated by reflections of structured light off the surface profile of the anatomy. The 3D surface scan may be used during intra-operative surgical navigation by a localization system. Optionally, a pre-operative medical image may also be registered to the localization system or used to enhance the 3D surface scan.

Abstract: Systems and methods are described herein to generate a 3D surface scan of a surface profile of a patient's anatomy. The 3D surface scan may be generated by reflections of structured light off the surface profile of the anatomy. The 3D surface scan may be used during intra-operative surgical navigation by a localization system. Optionally, a pre-operative medical image may also be registered to the localization system or used to enhance the 3D surface scan.

Abstract: Systems and methods are described herein to generate a 3D surface scan of a surface profile of a patient's anatomy. The 3D surface scan may be generated by reflections of structured light off the surface profile of the anatomy. The 3D surface scan may be used during intra-operative surgical navigation by a localization system. Optionally, a pre-operative medical image may also be registered to the localization system or used to enhance the 3D surface scan.

Abstract: Systems and methods are described herein to generate a 3D surface scan of a surface profile of a patient's anatomy. The 3D surface scan may be generated by reflections of structured light off the surface profile of the anatomy. The 3D surface scan may be used during intra-operative surgical navigation by a localization system. Optionally, a pre-operative medical image may also be registered to the localization system or used to enhance the 3D surface scan.

Abstract: The present application relates to systems and methods used to characterize or verify the accuracy of a tracker comprising optically detectable features. The tracker may be used in spatial localization using an optical sensor. Characterization results in the calculation of a Tracker Definition that includes geometrical characteristics of the tracker. Verification results in an assessment of accuracy of a tracker against an existing Tracker Definition.

Abstract: The present application relates to systems and methods used to characterize or verify the accuracy of a tracker comprising optically detectable features. The tracker may be used in spatial localization using an optical sensor. Characterization results in the calculation of a Tracker Definition that includes geometrical characteristics of the tracker. Verification results in an assessment of accuracy of a tracker against an existing Tracker Definition.

Abstract: The present application relates to systems and methods used to characterize or verify the accuracy of a tracker comprising optically detectable features. The tracker may be used in spatial localization using an optical sensor. Characterization results in the calculation of a Tracker Definition that includes geometrical characteristics of the tracker. Verification results in an assessment of accuracy of a tracker against an existing Tracker Definition.

Abstract: The present application relates to systems and methods used to characterize or verify the accuracy of a tracker comprising optically detectable features. The tracker may be used in spatial localization using an optical sensor. Characterization results in the calculation of a Tracker Definition that includes geometrical characteristics of the tracker. Verification results in an assessment of accuracy of a tracker against an existing Tracker Definition.

Abstract: The present application relates to systems and methods used to characterize or verify the accuracy of a tracker comprising optically detectable features. The tracker may be used in spatial localization using an optical sensor. Characterization results in the calculation of a Tracker Definition that includes geometrical characteristics of the tracker. Verification results in an assessment of accuracy of a tracker against an existing Tracker Definition.

Abstract: The present application relates to systems and methods used to characterize or verify the accuracy of a tracker comprising optically detectable features. The tracker may be used in spatial localization using an optical sensor. Characterization results in the calculation of a Tracker Definition that includes geometrical characteristics of the tracker. Verification results in an assessment of accuracy of a tracker against an existing Tracker Definition.

Abstract: Systems and methods are described herein to generate a 3D surface scan of a surface profile of a patient's anatomy. The 3D surface scan may be generated by reflections of structured light off the surface profile of the anatomy. The 3D surface scan may be used during intra-operative surgical navigation by a localization system. Optionally, a pre-operative medical image may also be registered to the localization system or used to enhance the 3D surface scan.

Abstract: The present application relates to systems and methods used to characterize or verify the accuracy of a tracker comprising optically detectable features. The tracker may be used in spatial localization using an optical sensor. Characterization results in the calculation of a Tracker Definition that includes geometrical characteristics of the tracker. Verification results in an assessment of accuracy of a tracker against an existing Tracker Definition.

Abstract: An optical see-through (OST) head-mounted display (HMD) uses a calibration matrix having a fixed sub-set of adjustable parameters within all its parameters. Initial values for the calibration matrix are based on a model head. A predefined set of incremental adjustment values is provided for each adjustable parameter. During calibration, the calibration matrix is cycled through its predefined incremental parameter changes, and a virtual object is projected for each incremental change. The resultant projected virtual object is aligned to a reference real object, and the projected virtual object having the best alignment is identified. The setting values of the calibration matrix that resulted in the best aligned virtual object are deemed the final calibration matrix to be used with the OST HMD.

Abstract: The present application relates to systems and methods used to characterize or verify the accuracy of a tracker comprising optically detectable features. The tracker may be used in spatial localization using an optical sensor. Characterization results in the calculation of a Tracker Definition that includes geometrical characteristics of the tracker. Verification results in an assessment of accuracy of a tracker against an existing Tracker Definition.

Abstract: Aspects of the present invention comprise holocam systems and methods that enable the capture and streaming of scenes. In embodiments, multiple image capture devices, which may be referred to as “orbs,” are used to capture images of a scene from different vantage points or frames of reference. In embodiments, each orb captures three-dimensional (3D) information, which is preferably in the form of a depth map and visible images (such as stereo image pairs and regular images). Aspects of the present invention also include mechanisms by which data captured by two or more orbs may be combined to create one composite 3D model of the scene. A viewer may then, in embodiments, use the 3D model to generate a view from a different frame of reference than was originally created by any single orb.

Abstract: An optical see-through (OST) head-mounted display (HMD) uses a calibration matrix having a fixed sub-set of adjustable parameters within all its parameters. Initial values for the calibration matrix are based on a model head. A predefined set of incremental adjustment values is provided for each adjustable parameter. During calibration, the calibration matrix is cycled through its predefined incremental parameter changes, and a virtual object is projected for each incremental change. The resultant projected virtual object is aligned to a reference real object, and the projected virtual object having the best alignment is identified. The setting values of the calibration matrix that resulted in the best aligned virtual object are deemed the final calibration matrix to be used with the OST HMD.

Abstract: Aspects of the present invention comprise holocam systems and methods that enable the capture and streaming of scenes. In embodiments, multiple image capture devices, which may be referred to as “orbs,” are used to capture images of a scene from different vantage points or frames of reference. In embodiments, each orb captures three-dimensional (3D) information, which is preferably in the form of a depth map and visible images (such as stereo image pairs and regular images). Aspects of the present invention also include mechanisms by which data captured by two or more orbs may be combined to create one composite 3D model of the scene. A viewer may then, in embodiments, use the 3D model to generate a view from a different frame of reference than was originally created by any single orb.

Abstract: An adequate solution for computer vision applications is arrived at more efficiently and, with more automation, enables users with limited or no special image processing and pattern recognition knowledge to create reliable vision systems for their applications. Computer rendering of CAD models is used to automate the dataset acquisition process and labeling process. In order to speed up the training data preparation while maintaining the data quality, a number of processed samples are generated from one or a few seed images.

Abstract: An adequate solution for computer vision applications is arrived at more efficiently and, with more automation, enables users with limited or no special image processing and pattern recognition knowledge to create reliable vision systems for their applications. Computer rendering of CAD models is used to automate the dataset acquisition process and labeling process. In order to speed up the training data preparation while maintaining the data quality, a number of processed samples are generated from one or a few seed images.

Abstract: An automated printout inspection system identifies glyphs in an image by calculating a connectedness score for each foreground pixel, and comparing this score with a specified threshold. The system further generates training images by simulating printouts from an impact printer, including the specifying of specific error types and their magnitudes. The simulated printouts are combined with scan images of real-world printout to train an automated printout inspection system. The inspection results of the automated system are compared with inspection results from human inspectors, and test parameters of the automated system are adjusted so that it renders inspection results within a specified range of the average human inspector.