LiDAR Point Cloud Encoding Using Reflection Model
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Solution Overview
Problem
In LiDAR technology, the encoding efficiency of 3D point cloud data with irregular surfaces is compromised due to varying reflected light intensities, leading to decreased prediction accuracy and encoding efficiency, especially when the distance between points is short.
Innovation Solution
An information processing apparatus and method that utilizes a reflection model to generate a predictive residual by decoding encoded data, deriving coefficients, and performing prediction processing to enhance encoding efficiency by accounting for surface orientation changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If predictive coding utilizing correlations between neighbor points is used, then encoding efficiency is improved for regular surfaces, but prediction accuracy decreases and encoding efficiency decreases for irregular surfaces
Solution Approach 1:
The patent changes the prediction model from simple spatial correlation to a physics-based reflection model that accounts for surface orientation parameters (normal vectors, incident angles). This parameter transformation allows accurate prediction of reflected light intensity even on irregular surfaces by considering the physical laws of light reflection rather than relying solely on spatial proximity correlations.
Solution Approach 2:
The patent introduces a reflection model as an intermediary between the raw point cloud data and the predictive coding process. This reflection model acts as a mediator that translates geometric surface properties into expected reflected light intensity values, enabling accurate prediction without directly relying on neighbor point correlations alone.
2Device complexity
If simple neighbor point correlation is used for prediction, then device complexity is reduced, but encoding efficiency decreases for irregular surfaces
Solution Approach 1:
The patent transforms the prediction approach by changing from using simple spatial coordinates to using physical parameters (surface normal vectors, light incident angles, reflection coefficients). This parameter change enables accurate encoding for irregular surfaces while maintaining manageable complexity through efficient calculation methods.
Solution Approach 2:
The reflection model utilizes intrinsic properties of the point cloud data itself (geometric information, surface orientation) to generate predictions, eliminating the need for external complex models. The system serves itself by using the data's own geometric characteristics to drive the prediction process.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution reduces the impact of surface orientation changes, thereby improving prediction accuracy and encoding efficiency for 3D point cloud data with irregular surfaces.
Implementation Method 1
a predicted value of the reflected light intensity generated by using a reflection model of light on a surface of the object
Data Source
AI summary
There is provided an information processing apparatus and method to make it possible to reduce a decrease in encoding efficiency. A predictive residual that is a difference between a reflected light intensity that is attribute data of a point cloud representing an object having a three-dimensional shape as a set of points and a predicted value of the reflected light intensity generated by using a reflection model of light on a surface of the object is generated by decoding encoded data of the predictive residual, a coefficient of the reflection model is derived, a predicted value is derived by performing prediction processing by using the reflection model and the coefficient, and the reflected light intensity is generated by adding the predictive residual obtained by decoding the encoded data and the derived predicted value. The present disclosure can be applied to, for example, an information processing apparatus, an electronic device, an image processing method, a program or the like.