Apple inc. (20240127491). Improved Predictive Coding for Point Cloud Compression simplified abstract
Contents
- 1 Improved Predictive Coding for Point Cloud Compression
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 Improved Predictive 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
Improved Predictive Coding for Point Cloud Compression
Organization Name
Inventor(s)
Khaled Mammou of Vancouver (CA)
Alexandros Tourapis of Los Gatos CA (US)
Improved Predictive Coding for Point Cloud Compression - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240127491 titled 'Improved Predictive Coding for Point Cloud Compression
Simplified Explanation
The patent application describes a system that receives encoded data related to points in a point cloud, including a prediction tree generated based on spatial information and sensor properties. The system decodes the data to determine spatial coordinates of the points and quantization parameters.
- Prediction tree based on spatial information and sensor properties
- Decoding of data to determine spatial coordinates and quantization parameters
- Generation of second data based on the first data
Potential Applications
The technology could be applied in various fields such as autonomous vehicles, robotics, augmented reality, and 3D mapping.
Problems Solved
This technology solves the problem of efficiently encoding and decoding spatial information from point clouds, enabling accurate representation of 3D environments.
Benefits
The system allows for the accurate reconstruction of 3D environments, leading to improved navigation, object recognition, and mapping capabilities.
Potential Commercial Applications
Potential commercial applications include autonomous driving systems, virtual reality applications, 3D modeling software, and industrial automation.
Possible Prior Art
One possible prior art could be existing systems for encoding and decoding spatial information in point clouds, but the specific approach outlined in this patent application may offer unique advantages.
Unanswered Questions
How does this technology compare to existing point cloud encoding methods?
This technology appears to offer a more efficient and accurate way of encoding and decoding spatial information from point clouds compared to existing methods. It would be interesting to see a direct comparison of performance metrics such as data compression ratios and reconstruction accuracy.
What are the potential limitations of this technology in real-world applications?
While the patent application outlines a promising approach to encoding and decoding spatial information from point clouds, there may be limitations in terms of computational complexity, scalability, and robustness in real-world scenarios. Further testing and validation in practical applications would be necessary to assess these potential limitations.
Original Abstract Submitted
a system receives encoded data regarding a points in a point cloud. the data includes a prediction tree having a nodes generated based on spatial information regarding the points and properties of a sensor system that obtained the spatial information. a value of each node represents first spatial coordinates of a respective one of the points according to a first coordinate system, and the value of at least a first node in the prediction tree is determined based on ancestor nodes of the first node and the properties of the sensor system. the system decodes the data to determine first data, including the first spatial coordinates of at least some of the points, and quantization parameters associated with the first spatial coordinates. the system determines second data based on the first data, including second spatial coordinates of at least some of the points according to a second coordinate system.
