US Patent Application 18303373. RESIDUAL PREDICTION FOR GEOMETRY POINT CLOUD COMPRESSION simplified abstract
Contents
RESIDUAL PREDICTION FOR GEOMETRY POINT CLOUD COMPRESSION
Organization Name
Inventor(s)
Adarsh Krishnan Ramasubramonian of Irvine CA (US)
Geert Van Der Auwera of San Diego CA (US)
Bappaditya Ray of San Diego CA (US)
Luong Pham Van of San Diego CA (US)
Marta Karczewicz of San Diego CA (US)
RESIDUAL PREDICTION FOR GEOMETRY POINT CLOUD COMPRESSION - A simplified explanation of the abstract
- This abstract for appeared for US patent application number 18303373 Titled 'RESIDUAL PREDICTION FOR GEOMETRY POINT CLOUD COMPRESSION'
Simplified Explanation
This abstract describes a device that can decode a point cloud, which is a collection of data points in a three-dimensional space. The device includes a memory to store the point cloud data and one or more processors to perform various operations.
The device can decode a residual value, which is a measure of the difference between the predicted position of a point and its actual position in the point cloud. It can determine whether residual prediction should be applied to a current point in the point cloud. If so, it calculates a residual predictor and adds it to the residual value to obtain a final residual value.
The device also determines a predictor that is used to predict the position of the current point in the point cloud. It then uses this predictor along with the final residual value to determine the accurate position of the current point.
In summary, this device is designed to decode a point cloud by applying residual prediction and using predictors to accurately determine the positions of the data points.
Original Abstract Submitted
A device for decoding a point cloud includes a memory configured to store data representing the point cloud and one or more processors implemented in circuitry and configured to: decode a residual value; determine whether residual prediction is to be applied to a current point of the point cloud; in response to determining that residual prediction is to be applied to the current point of the point cloud: determine a residual predictor and add the residual predictor to the residual value to determine a final residual value; determine a predictor used to predict a current point of the point cloud; and use the predictor and the final residual value to determine a position of the current point.
