Carnegie Mellon University

Kaarta, Inc.

Steven Huber

Ji Zhang

Calvin Wade Sheen

Ethan Abramson

Brian Boyle

A method includes acquiring with a scanning device a scan frame including a point cloud comprising a first plurality of points and describing a spatial characteristic of an environment, attributing each of the first plurality of points with a spatial confidence metric, discarding a portion of the first plurality of points when the spatial confidence metric of at least one of the first plurality of points is below a predefined threshold value and directing a user of the scanning device to acquire a second point cloud approximately coincident with the discarded portion of the first plurality of points.

Methods and systems for real or near real-time point cloud map data confidence evaluation

A method includes creating a point cloud model of an environment, applying at least one filter to the point cloud model to produce a filtered model of the environment and defining a plane in the filtered model corresponding to a horizontal expanse associated with a floor of the environment.

Methods and systems for auto-leveling of point clouds and 3D models

A method of pose calculation for a portable three-dimensional scanning device including a first sensor and a second sensor the method including utilizing data from the first sensor and data from the second sensor to acquire data defining six degrees of freedom of the scanning device to optimize a first pose calculation, receiving data comprising one of data from the first sensor and data from the second sensor, selecting a subset of the six degrees of freedom of the scanning device, utilizing the data from the first sensor and the received data for the selected subset of six degrees of freedom to optimize a second pose, wherein the unselected degrees of freedom are retained from the first pose and storing received data associated with the second camera pose in a point cloud database.

Systems and methods for improvements in scanning and mapping

A method includes determining a mesh representing an environment based, at least in part, on a point cloud the mesh comprising a plurality of triangles each having a normal vector, acquiring one or more images of the environment wherein each of the one or more images is attributed with a view position and a view angle and applying the one or more images to the mesh.

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Pittsburgh, PA, United States of America

Steven Huber