View source for 18158135. SECONDARY COMPONENT ATTRIBUTE CODING FOR GEOMETRY-BASED POINT CLOUD COMPRESSION (G-PCC) simplified abstract (QUALCOMM Incorporated)

=SECONDARY COMPONENT ATTRIBUTE CODING FOR GEOMETRY-BASED POINT CLOUD COMPRESSION (G-PCC)=


==Organization Name==

[[:Category:QUALCOMM Incorporated|QUALCOMM Incorporated]]


[[Category:QUALCOMM Incorporated]]

==Inventor(s)==

[[:Category:Adarsh Krishnan Ramasubramonian of Irvine CA (US)|Adarsh Krishnan Ramasubramonian of Irvine CA (US)]][[Category:Adarsh Krishnan Ramasubramonian of Irvine CA (US)]]

[[:Category:Bappaditya Ray of San Diego CA (US)|Bappaditya Ray of San Diego CA (US)]][[Category:Bappaditya Ray of San Diego CA (US)]]

[[:Category:Geert Van Der Auwera of San Diego CA (US)|Geert Van Der Auwera of San Diego CA (US)]][[Category:Geert Van Der Auwera of San Diego CA (US)]]

[[:Category:Louis Joseph Kerofsky of San Diego CA (US)|Louis Joseph Kerofsky of San Diego CA (US)]][[Category:Louis Joseph Kerofsky of San Diego CA (US)]]

[[:Category:Marta Karczewicz of San Diego CA (US)|Marta Karczewicz of San Diego CA (US)]][[Category:Marta Karczewicz of San Diego CA (US)]]

==SECONDARY COMPONENT ATTRIBUTE CODING FOR GEOMETRY-BASED POINT CLOUD COMPRESSION (G-PCC) - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18158135 titled 'SECONDARY COMPONENT ATTRIBUTE CODING FOR GEOMETRY-BASED POINT CLOUD COMPRESSION (G-PCC)

==Simplified Explanation==

The patent application describes a method for decoding point cloud data using Quantization Parameter (QP) values. 

* The method starts by decoding an initial QP value from an attribute parameter set.
* It then determines a first QP value for the first component of the attribute based on the initial QP value.
* A QP offset value is determined for the second component of the attribute.
* The method further determines a second QP value for the second component based on the first QP value and the QP offset value.
* Finally, the point cloud data is decoded using the first and second QP values.

Potential applications of this technology:

* Point cloud data compression and transmission
* 3D modeling and visualization
* Augmented reality and virtual reality applications

Problems solved by this technology:

* Efficient decoding of point cloud data
* Accurate representation of attribute components
* Reduction in data size for storage and transmission

Benefits of this technology:

* Improved efficiency in decoding point cloud data
* Enhanced accuracy in representing attribute components
* Reduced storage and bandwidth requirements for point cloud data


==Original Abstract Submitted==

In some examples, a method of decoding a point cloud includes decoding an initial QP value from an attribute parameter set. The method also includes determining a first QP value for a first component of an attribute of point cloud data from the initial QP value. The method further includes determining a QP offset value for a second component of the attribute of the point cloud data and determining a second QP value for the second component of the attribute from the first QP value and from the QP offset value. The method includes decoding the point cloud data based on the first QP value and further based on the second QP value.



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[[Category:H04N19/124]]