18545966. In-tree geometry quantization of point clouds simplified abstract (Apple Inc.)
Contents
- 1 In-tree geometry quantization of point clouds
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 In-tree geometry quantization of point clouds - 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
In-tree geometry quantization of point clouds
Organization Name
Inventor(s)
Khaled Mammou of Vancouver (CA)
Fabrice A. Robinet of Sunnyvale CA (US)
In-tree geometry quantization of point clouds - A simplified explanation of the abstract
This abstract first appeared for US patent application 18545966 titled 'In-tree geometry quantization of point clouds
Simplified Explanation
The abstract describes a method for encoding and quantizing point cloud data using a tree data structure and an exponential function for determining quantization step size.
- Receiving a plurality of points representing a point cloud
- Encoding the position of each point in a three-dimensional space as a sequence of bits using a tree data structure
- Partitioning the bit sequences into first and second portions
- Quantizing the second portions of bits based on an exponential function with a quantization parameter value
- Generating a data structure representing the point cloud with quantized second portions of bits
Potential Applications
This technology could be applied in various fields such as:
- 3D modeling and rendering
- Geographic information systems (GIS)
- Virtual reality and augmented reality
Problems Solved
This technology addresses the following issues:
- Efficient encoding and quantization of large point cloud data
- Reduction of storage and transmission requirements for point cloud information
- Improved visualization and analysis of 3D spatial data
Benefits
The benefits of this technology include:
- Enhanced data compression and storage efficiency
- Precise representation of point cloud data with reduced memory usage
- Faster processing and rendering of 3D spatial information
Potential Commercial Applications
The technology could find commercial applications in:
- Software development for 3D mapping and visualization
- Autonomous vehicles for processing LiDAR data
- Cloud computing services for handling large-scale point cloud datasets
Possible Prior Art
One possible prior art for this technology could be the use of octrees for encoding and compressing 3D spatial data. Octrees are tree data structures commonly used in computer graphics and spatial indexing for efficient representation of volumetric data.
Original Abstract Submitted
An example method includes receiving a plurality of points that represent a point cloud; representing a position of the point in each dimension of a three-dimensional space as a sequence of bits, where the position of the point is encoded according to a tree data structure; partitioning at least one of the sequences of bits into a first portion of bits and a second portion of bits; quantizing each of the second portions of bits according to a quantization step size, where the quantization step size is determined according to an exponential function having a quantization parameter value as an input and the quantization step size as an output; and generating a data structure representing the point cloud and including the quantized second portions of bits.
