18518765. THREE-DIMENSIONAL DATA ENCODING METHOD, THREE-DIMENSIONAL DATA DECODING METHOD, THREE-DIMENSIONAL DATA ENCODING METHOD, THREE-DIMENSIONAL simplified abstract (Panasonic Intellectual Property Corporation of America)
Contents
- 1 THREE-DIMENSIONAL DATA ENCODING METHOD, THREE-DIMENSIONAL DATA DECODING METHOD, THREE-DIMENSIONAL DATA ENCODING METHOD, THREE-DIMENSIONAL
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 THREE-DIMENSIONAL DATA ENCODING METHOD, THREE-DIMENSIONAL DATA DECODING METHOD, THREE-DIMENSIONAL DATA ENCODING METHOD, THREE-DIMENSIONAL - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications of this Technology
- 1.6 Problems Solved by this Technology
- 1.7 Benefits of this Technology
- 1.8 Potential Commercial Applications of this Technology
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
THREE-DIMENSIONAL DATA ENCODING METHOD, THREE-DIMENSIONAL DATA DECODING METHOD, THREE-DIMENSIONAL DATA ENCODING METHOD, THREE-DIMENSIONAL
Organization Name
Panasonic Intellectual Property Corporation of America
Inventor(s)
THREE-DIMENSIONAL DATA ENCODING METHOD, THREE-DIMENSIONAL DATA DECODING METHOD, THREE-DIMENSIONAL DATA ENCODING METHOD, THREE-DIMENSIONAL - A simplified explanation of the abstract
This abstract first appeared for US patent application 18518765 titled 'THREE-DIMENSIONAL DATA ENCODING METHOD, THREE-DIMENSIONAL DATA DECODING METHOD, THREE-DIMENSIONAL DATA ENCODING METHOD, THREE-DIMENSIONAL
Simplified Explanation
The three-dimensional data encoding method described in the abstract involves determining the number of valid nodes in a three-dimensional point cloud data structure and encoding attribute information based on certain criteria. Here is a simplified explanation of the patent application:
- The method involves counting valid nodes in a three-dimensional point cloud data structure.
- If the count meets a predetermined threshold, encoding of attribute information is performed.
- Encoding includes a prediction process using parent nodes from the same layer.
Potential Applications of this Technology
This technology could be applied in various fields such as:
- 3D modeling and rendering
- Geographic information systems
- Augmented reality
Problems Solved by this Technology
This technology addresses the following issues:
- Efficient encoding and storage of three-dimensional data
- Predictive encoding for attribute information
- Optimization of data processing in point cloud structures
Benefits of this Technology
The benefits of this technology include:
- Improved data compression in three-dimensional structures
- Enhanced prediction capabilities for attribute encoding
- Streamlined processing of large-scale point cloud data
Potential Commercial Applications of this Technology
A potential commercial application for this technology could be in:
- Cloud computing services for 3D data processing
- Software development for 3D visualization tools
- Data analytics platforms for spatial data processing
Possible Prior Art
One possible prior art related to this technology is the use of predictive encoding techniques in image and video compression algorithms. These methods aim to reduce data redundancy and improve compression efficiency.
What are the specific industries that could benefit from this technology?
Industries such as:
- Architecture and construction
- Virtual reality and gaming
- Autonomous vehicles
How does this technology compare to existing data encoding methods in terms of efficiency and accuracy?
This technology offers:
- Improved efficiency in encoding three-dimensional data
- Enhanced accuracy in predicting attribute information
- Potential for better compression ratios compared to traditional methods
Original Abstract Submitted
A three-dimensional data encoding method includes: determining whether a first valid node count is greater than or equal to a first threshold value predetermined, the first valid node count being a total number of valid nodes that are nodes each including a three-dimensional point, the valid nodes being included in first nodes belonging to a layer higher than a layer of a current node in an N-ary tree structure of three-dimensional points included in point cloud data, N being an integer greater than or equal to 2; and, when the first valid node count is greater than or equal to the first threshold value, performing first encoding on attribute information of the current node, the first encoding including a prediction process in which second nodes are used, the second nodes including a parent node of the current node and belonging to a same layer as the parent node.
