Verizon Patent and Licensing Inc.

Syed B Aziz

Vidhya Seran

Jerry Gamble, Jr

Natasha Avinash Shah

Peter Brockmann

Aleena Taufiq

An illustrative point cloud compression system accesses an input point cloud dataset representative of a point cloud comprising a plurality of points. The point cloud compression system identifies a first attribute dataset and a second attribute dataset within the input point cloud dataset. Based on an application of a transform algorithm to the first and second attribute datasets, respectively, the point cloud compression system generates 1) a first low-frequency component and a first high-frequency component of the first attribute dataset, and 2) a second low-frequency component and a second high-frequency component of the second attribute dataset. The point cloud compression system then generates an output point cloud dataset that prioritizes both the first and second low-frequency components above both the first and second high-frequency components. Corresponding methods and systems are also disclosed.

Methods and systems for scalable compression of point cloud data

One or more computing devices, systems, and/or methods for elevation tracking of devices are provided. Barometric pressure data points and elevation data points associated with a set of barometric measurement devices proximate a device are obtained. An interpolated field of barometric pressure is generated using the barometric pressure data points and the elevation data points. x, y location coordinates of the device are projected onto the interpolated field as a projected point within the interpolated field. Barometric leveling is executed upon a device barometric pressure value provided by the device and a barometric pressure data point at the projected point to determine a relative height difference between the device and the projected point. An elevation of the device is determined based upon the relative height difference.

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North Grafton, MA, United States of America

Syed B Aziz