View source for 17937381. Point Cloud Compression simplified abstract (Apple Inc.)

=Point Cloud Compression=


==Organization Name==

[[:Category:Apple Inc.|Apple Inc.]]


[[Category:Apple Inc.]]

==Inventor(s)==

[[:Category:Khaled Mammou of Danville CA (US)|Khaled Mammou of Danville CA (US)]][[Category:Khaled Mammou of Danville CA (US)]]

[[:Category:Fabrice A. Robinet of Sunnyvale CA (US)|Fabrice A. Robinet of Sunnyvale CA (US)]][[Category:Fabrice A. Robinet of Sunnyvale CA (US)]]

==Point Cloud Compression - A simplified explanation of the abstract==


This abstract first appeared for US patent application 17937381 titled 'Point Cloud Compression

==Simplified Explanation==

The patent application describes a system that compresses and decompresses attribute information for a point cloud. 

* The system includes an encoder and a decoder.
* The encoder compresses attribute information for the point cloud, while the decoder decompresses the compressed attribute information.
* The compressed attribute information file includes attribute values for at least one starting point and attribute correction values.
* Attribute values are predicted based on attribute values of neighboring points and distances between the particular point and the neighboring points.
* The predicted attribute values are compared to attribute values of the original point cloud to determine attribute correction values.
* The decoder follows a similar prediction process as the encoder and corrects predicted values using attribute correction values.

== Potential Applications ==
This technology has potential applications in various fields, including:

* 3D modeling and visualization
* Virtual reality and augmented reality
* Autonomous vehicles and robotics
* Geographical information systems (GIS)
* Medical imaging and diagnostics

== Problems Solved ==
The technology addresses the following problems:

* Efficient compression of attribute information for point clouds
* Lossless compression and decompression of attribute values
* Prediction and correction of attribute values based on neighboring points
* Reduction of storage and transmission requirements for point cloud data

== Benefits ==
The technology offers several benefits, including:

* Reduced storage and bandwidth requirements for point cloud data
* Efficient compression and decompression of attribute information
* Accurate prediction and correction of attribute values
* Improved performance and efficiency in processing and analyzing point cloud data


==Original Abstract Submitted==

A system comprises an encoder configured to compress attribute information for a point cloud and/or a decoder configured to decompress compressed attribute information for the point cloud. Attribute values for at least one starting point are included in a compressed attribute information file and attribute correction values used to correct predicted attribute values are included in the compressed attribute information file. Attribute values are predicted based, at least in part, on attribute values of neighboring points and distances between a particular point for whom an attribute value is being predicted and the neighboring points. The predicted attribute values are compared to attribute values of a point cloud prior to compression to determine attribute correction values. A decoder follows a similar prediction process as an encoder and corrects predicted values using attribute correction values included in a compressed attribute information file.



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