18490467. ATTRIBUTE CODING FOR POINT CLOUD COMPRESSION simplified abstract (QUALCOMM Incorporated)
Contents
- 1 ATTRIBUTE CODING FOR POINT CLOUD COMPRESSION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 ATTRIBUTE CODING FOR POINT CLOUD COMPRESSION - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
ATTRIBUTE CODING FOR POINT CLOUD COMPRESSION
Organization Name
Inventor(s)
Anique Akhtar of San Diego CA (US)
Geert Van Der Auwera of San Diego CA (US)
Adarsh Krishnan Ramasubramonian of Irvine CA (US)
Marta Karczewicz of San Diego CA (US)
ATTRIBUTE CODING FOR POINT CLOUD COMPRESSION - A simplified explanation of the abstract
This abstract first appeared for US patent application 18490467 titled 'ATTRIBUTE CODING FOR POINT CLOUD COMPRESSION
Simplified Explanation
The method described in the abstract involves encoding point cloud data by first encoding geometry data of a source point cloud, then decoding it to generate reconstructed geometry data. An attribute recomputing process is performed on attribute data of the source point cloud based on the reconstructed geometry data to generate recomputed, reconstructed point cloud data, which is then encoded to generate an attribute bitstream.
- Receiving geometry data of a source point cloud for encoding.
- Encoding the geometry data to generate encoded geometry data of a target point cloud and a geometry bitstream.
- Decoding the encoded geometry data to generate reconstructed geometry data.
- Performing an attribute recomputing process on attribute data of the source point cloud based on the reconstructed geometry data.
- Encoding the recomputed, reconstructed point cloud data to generate an attribute bitstream.
Potential Applications
This technology could be applied in fields such as 3D modeling, virtual reality, augmented reality, and geographic information systems.
Problems Solved
This technology solves the problem of efficiently encoding and decoding point cloud data while preserving geometric and attribute information accurately.
Benefits
The benefits of this technology include improved data compression, faster data transmission, and more efficient storage of point cloud data.
Potential Commercial Applications
Potential commercial applications of this technology include data compression software, 3D scanning devices, virtual reality platforms, and GIS software.
Possible Prior Art
One possible prior art in this field is the use of various encoding techniques for point cloud data compression, such as octree-based methods and predictive coding algorithms.
Unanswered Questions
How does this method compare to existing point cloud data encoding techniques?
This method combines geometry and attribute data encoding processes, which may offer improved compression and reconstruction accuracy compared to traditional methods.
What are the computational requirements for implementing this encoding method?
The computational resources needed to perform the encoding and decoding processes efficiently are crucial for real-time applications.
Original Abstract Submitted
A method of encoding point cloud data includes receiving, for a first encoding process, geometry data of the point cloud data of a source point cloud; encoding, in accordance with the first encoding process, the geometry data to generate encoded geometry data of a target point cloud and a geometry bitstream; decoding the encoded geometry data to generate reconstructed geometry data; performing an attribute recomputing process on attribute data of the point cloud data of the source point cloud based on the reconstructed geometry data to generate recomputed, reconstructed point cloud data of the target point cloud; and encoding, in accordance with a second encoding process, the recomputed, reconstructed point cloud data to generate an attribute bitstream.
